Code accompanying "Observing formation and early evolution of contrails formed by IAGOS aircraft using high-resolution LEO satellite imagery"

This repository contains a Python toolkit for analyzing contrail formation and early evolution by matching data from three sources:

1. Aircraft Measurements - Real-time measurements of temperature, humidity, and emissions from In-service Aicraft for a Global Observing System (IAGOS) commercial aircraft.

2. Satellite Imagery - High-resolution images from Low Earth Orbit (LEO) satellites (Sentinel-2 and Landsat).

3. Weather Data - meteorological data (ECMWF Reanalysis v5 ERA5).

This repository contains a series of Python scripts to study the formation and early evolution of contrails produced by IAGOS aircraft using high-resolution LEO satellite imagery. The code aligns in space and time (collocates) the three datasets mentioned above, in order to understand when do contrails form and how they evolve in time, including their environmental impact.

More specifically, the ./src/iagos_toolkit contains scripts to:

• load and process aircraft flight trajectories from ADS-B (automatic dependent surveillance) data;

• calculate and retrieve atmospheric conditions at aircraft altitude and location;

• process satellite imagery to detect and measure contrails.

The notebooks provided in ./notebooks/ use the ./src/iagos_toolkit to reproduce the results published in Woldhuis et al. (2026) (see References). In order to execute all notebooks, download the full dataset from the 4TU.ResearchData archive (see also References). Keep in mind the full dataset size is +-50 GB. To reproduce most paper results without the full dataset, the file ./data/landsat_sentinel_collocations_20260216.csv can be used.