Nighttime Contrail Characterization from Multisource Lidar and Meteorological Observations

The present study provides a comprehensive nighttime contrail characterization combining Raman lidar, ADS-B flight data, and ECMWF ERA5 reanalysis over southern France. Observations of different case studies of contrail formation and development throughout their lifetimes provide valuable insights into the contrails’ morphological, microphysical, and optical properties, persistence, and dispersion. We present a multisource methodology to detect and characterize nighttime aircraft contrails over the Observatory of Haute-Provence (OHP) in France. The determination of contrail signatures was performed by applying sensitivity analyses by spatiotemporal thresholding and clustering for contrail detection. Optimizing the thresholds permits the improvement of contrail detection and the reduction of unnecessary noise. The optimal combination of these thresholds, which best reduces false positives and negatives, was SR = 2.1, time = 7.2 min, and altitude = 0.3 km. Subsequent merging of the spots produces persistent contrail signatures at altitudes of 8.7–10.3 km, with thicknesses of 0.1–1.1 km, widths of 2–2.8 km, and optical depths of 0.05–0.40. Contrail optical depth correlates significantly with geometrical thickness and width, which highlights the interplay between contrail morphology and ambient thermodynamic conditions. Our methodology demonstrates the value of combining lidar and flight data for contrail characterization using lidar measurements, flight data, and meteorological information.

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Publication Details

Journal
Remote Sensing
Published
2026-01-08
DOI
https://doi.org/10.3390/rs18020210
Primary Topic
Atmospheric aerosols and clouds
Type
article
Field-Weighted Citation Impact
0.00

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article

Nighttime Contrail Characterization from Multisource Lidar and Meteorological Observations

Abdanour Irbah, J.-L. BARAY, Frédéric Peyrin, Alain Sarkissian et al.
Remote Sensing
Atmospheric aerosols and clouds
article

Nighttime Contrail Characterization from Multisource Lidar and Meteorological Observations

Abdanour Irbah, J.-L. BARAY, Frédéric Peyrin, Alain Sarkissian, Dunya Alraddawi, Florian Mandija, S. Khaykin, Philippe Keckhut
article en

Abstract

The present study provides a comprehensive nighttime contrail characterization combining Raman lidar, ADS-B flight data, and ECMWF ERA5 reanalysis over southern France. Observations of different case studies of contrail formation and development throughout their lifetimes provide valuable insights into the contrails’ morphological, microphysical, and optical properties, persistence, and dispersion. We present a multisource methodology to detect and characterize nighttime aircraft contrails over the Observatory of Haute-Provence (OHP) in France. The determination of contrail signatures was performed by applying sensitivity analyses by spatiotemporal thresholding and clustering for contrail detection. Optimizing the thresholds permits the improvement of contrail detection and the reduction of unnecessary noise. The optimal combination of these thresholds, which best reduces false positives and negatives, was SR = 2.1, time = 7.2 min, and altitude = 0.3 km. Subsequent merging of the spots produces persistent contrail signatures at altitudes of 8.7–10.3 km, with thicknesses of 0.1–1.1 km, widths of 2–2.8 km, and optical depths of 0.05–0.40. Contrail optical depth correlates significantly with geometrical thickness and width, which highlights the interplay between contrail morphology and ambient thermodynamic conditions. Our methodology demonstrates the value of combining lidar and flight data for contrail characterization using lidar measurements, flight data, and meteorological information.

Remote SensingVol. 18(2)
Centre National de la Recherche Scientifique (FR), Université de Versailles Saint-Quentin-en-Yvelines (FR), Université Clermont Auvergne (FR), Université Paris-Saclay (FR), Sorbonne Université (FR), Observatoire de Physique du Globe de Clermont-Ferrand (FR), Institut Pierre-Simon Laplace (FR), Laboratoire de Météorologie Physique (FR), Laboratoire atmosphères, milieux, observations spatiales (FR)
European Centre for Medium-Range Weather Forecasts
Life below water
Openalex Percentile: Top 96%
Atmospheric aerosols and clouds
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