Assessing Contrail Radiative Effects: A Comparison of MTG Satellite Detections and Physics-Based Simulations

The increasing impact of aviation on global climate change underscores the critical need for accurate quantification of its environmental effects. Among them, persistent contrails and aviation-induced cloudiness are recognized as the most significant contributors, yet the quantification of their effects remains the most uncertain [1]. During the last decades, physics-based models, which involve the simulation of contrail formation, evolution, and radiative forcing by integrating aircraft specifications and meteorological data, have been the primary tools for large-scale quantification and estimation of contrail impacts [2]. Recently, data-driven methods that leverage neural networks for satellite identification combined with radiative transfer (RT) models to estimate shortwave and longwave cloud radiative effects have emerged as reliable alternatives due to their strong foundation in observational data [3]. The alignment between these two approaches, data-driven and physics-driven, has not been thoroughly explored in the literature, despite its critical importance for ensuring consistency and reliability in studies aimed at reducing uncertainties in the assessment of contrail-related climate impacts. In this work, we perform a comparison over four full days, focusing primarily on the European domain as captured by the Flexible Combined Imager (FCI) onboard the Meteosat Third Generation (MTG)-I geostationary satellite. We compare contrail effects obtained applying an RT model on segmented contrails with a tailored neural network, with per-trajectory contrail effects simulated using the Contrail Cirrus Prediction model (CoCiP) [4] and Automatic Dependent Surveillance—Broadcast (ADS-B) flight data across multiple timeframes. This flight data accounts for time intervals extending up to two hours prior to each satellite image capture, to account for the delay in contrail visibility on the satellite. To address meteorological uncertainties, an ensemble approach uses 10 weather scenarios derived from ERA5 reanalysis data obtained from the European Centre for Medium-Range Weather Forecasts (ECMWF). Since RT simulations provide only instantaneous forcing, detected contrails in the satellite imagery are tracked over time, and the accumulated radiative forcing is calculated and compared to that of the simulated contrails. Overall, this study offers valuable insights into the agreement between observational and physics-based approaches across several key aspects: I) contrail formation, II) contrail lifetime, and III) contrail climate impacts.

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