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Contrail-to-Flight Attribution Using Ground Visible Cameras and Flight Surveillance Data

Ramon Dalmau, Gabriel Jarry, Philippe Very

TL;DR

This work tackles the challenge of contrail-to-flight attribution, essential for validating contrail-climate models, by leveraging high-resolution ground-based observations. It introduces a modular framework that fuses GVCCS ground camera data, ADS-B flight trajectories, and ERA5 meteorology to generate theoretical contrails via dry advection and physics-based models, then matches observed contrails to candidate flights through temporal filtering, geometric distances, memory aggregation, probabilistic scoring, and assignment. The approach is instantiated with concrete choices for geometry, distance metrics, and an EWMA-based memory, achieving high attribution accuracy for newly forming contrails on the GVCCS dataset (e.g., up to ~94% correct among new contrails) while identifying limitations in distinguishing old contrails from new ones. The framework provides a strong baseline for contrail validation and calibration of climate models and offers promising extensions, including incorporating altitude cues and linking ground- and satellite-observed contrails for continuous tracking.

Abstract

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.

Contrail-to-Flight Attribution Using Ground Visible Cameras and Flight Surveillance Data

TL;DR

This work tackles the challenge of contrail-to-flight attribution, essential for validating contrail-climate models, by leveraging high-resolution ground-based observations. It introduces a modular framework that fuses GVCCS ground camera data, ADS-B flight trajectories, and ERA5 meteorology to generate theoretical contrails via dry advection and physics-based models, then matches observed contrails to candidate flights through temporal filtering, geometric distances, memory aggregation, probabilistic scoring, and assignment. The approach is instantiated with concrete choices for geometry, distance metrics, and an EWMA-based memory, achieving high attribution accuracy for newly forming contrails on the GVCCS dataset (e.g., up to ~94% correct among new contrails) while identifying limitations in distinguishing old contrails from new ones. The framework provides a strong baseline for contrail validation and calibration of climate models and offers promising extensions, including incorporating altitude cues and linking ground- and satellite-observed contrails for continuous tracking.

Abstract

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.
Paper Structure (22 sections, 4 equations, 7 figures)

This paper contains 22 sections, 4 equations, 7 figures.

Table of Contents

  1. Introduction
  2. State of the Art
  3. Data
  4. Observed Contrails
  5. Flight Trajectory Data
  6. Meteorological Data
  7. Contrail-to-Flight Attribution Framework
  8. Temporal Filtering
  9. Geometric Distance
  10. Memory-Aware Aggregation
  11. Distances to Probabilities
  12. Assignment
  13. Particular Implementation
  14. Geometries
  15. Annotations
  16. ...and 7 more sections

Figures (7)

  • Figure 1: Illustrative sequence of frames on 26 April 2024.
  • Figure 2: Annotations for the illustrative sequence shown in Fig. \ref{['fig:raw']}. The sequence includes two new and one old contrails.
  • Figure 3: Theoretical contrails generated by a simple dry advection model for the flights crossing the camera’s field of view during the sequence shown in Fig. \ref{['fig:raw']}. Dashed lines indicate the actual flight trajectories, while solid multi-polygons represent the simulated contrails.
  • Figure 4: Conversion of an annotated contrail into a geometry.
  • Figure 5: Illustrative examples of attributed contrails.
  • ...and 2 more figures