Contrail-to-Flight Attribution Using Ground Visible Cameras and Flight Surveillance Data
This addresses the need for validating contrail climate models, though it is incremental as it builds on existing datasets and methods.
The paper tackles the problem of attributing observed contrails to specific flights by developing a modular framework using ground-based cameras and flight surveillance data, achieving a baseline for linking contrails to their source flights.
Aviation's non-CO2 effects, particularly contrails, are a significant contributor to its climate impact. Persistent contrails can evolve into cirrus-like clouds that trap outgoing infrared radiation, with radiative forcing potentially comparable to or exceeding that of aviation's CO2 emissions. While physical models simulate contrail formation, evolution and dissipation, validating and calibrating these models requires linking observed contrails to the flights that generated them, a process known as contrail-to-flight attribution. Satellite-based attribution is challenging due to limited spatial and temporal resolution, as contrails often drift and deform before detection. In this paper, we evaluate an alternative approach using ground-based cameras, which capture contrails shortly after formation at high spatial and temporal resolution, when they remain thin, linear, and visually distinct. Leveraging the ground visible camera contrail sequences (GVCCS) dataset, we introduce a modular framework for attributing contrails observed using ground-based cameras to theoretical contrails derived from aircraft surveillance and meteorological data. The framework accommodates multiple geometric representations and distance metrics, incorporates temporal smoothing, and enables flexible probability-based assignment strategies. This work establishes a strong baseline and provides a modular framework for future research in linking contrails to their source flight.