Alternative aviation fuels represent a promising approach to reduce contrails climate effect. In the frame of VOLCAN (“VOL avec Carburants Alternatifs Nouveaux”) project (DGAC funding, collaboration with AIRBUS, Safran Aircraft Engines and DLR, financed by Neofuels), the influence of Sustainable Alternative Fuels (SAF) composition on exhaust plumes emission, and therefore on contrails, is investigated using the 1D detailed microphysical code MoMiE (Modèle Microphysique pour Effluents) developed at ONERA1,2. The VOLCAN measurement campaigns have been able to provide estimations of ice particle number emission indexes within contrails formed by different fuel types (classical kerosene Jet A-1 and biofuel HEFA) and different combustion modes (“rich” and “lean” burn). These are complementing the observations obtained for Sustainable Alternative Fuels with Emission and “CLimate Impact of alternative Fuels” (ECLIF) campaigns3,4, recently compared to the results of the “Aerosol and Contrail Microphysics” (ACM) model developed at the University of Albany5.
In its most recent version ONERA’s code MoMiE has been adapted to Sustainable Alternative Fuels (SAF)2. It includes heterogenous freezing with soot activation by sulfur and organic species, as well as homogeneous freezing of liquid droplets of hydrated sulfates and organics, accounting for the competition between both nucleation modes. Chemiionization, brownian coagulation of particles, ice sublimation and condensation are also represented. The code computes the different aerosols distributions (size and number) of sulfates, organics, dry soot, activated soot, and ice particles, homogeneously (no solid nucleus) and heterogeneously (soot solid nucleus) formed.
The work proposed here aims first at presenting and analyzing the results obtained with the model in comparison to some of the VOLCAN measurements. The sensitivity of contrail formation to the different fuel types, combustion modes and emission characteristics, as ion emission index, which is known to play a significant role in the coagulation process, are studied. The model is also confronted to the ECLIF measurements3,4 and the microphysics model results from University of Albany5. Advancement and results of this study will be presented and discussed during the conference.
1Vancassel X. et al., Numerical simulation of aerosols in an aircraft wake using a 3D LES solver and a detailed microphysical model, International Journal of Sustainable Aviation, 2014
2Rojo C. et al., Impact of alternative jet fuels on aircraft-induced aerosols, Fuel, 2014
3Voigt C. et al., Cleaner burning aviation fuels can reduce contrail cloudiness, communications earth & environment, 2021
4Märkl R. S. et al., Powering aircraft with 100% sustainable aviation fuel reduces ice crystals in contrails, Atmospheric Chemistry and Physics, 2024
5Yu F. et al., Revisiting Contrail Ice Formation: Impact of Primary Soot Particle Sizes and Contribution of Volatile Particles, Environmental Science & Technology, 2024
How to cite: Vals, M., Bonne, N., Ortega, I., Seeliger, K., Renard, C., Voigt, C., Sauer, D., Märkl, R., Dischl, R., Kaufmann, S., Harlass, T., Marsing, A., Roiger, A., Greslin, E., and Roche, A.: Modeling the formation of contrails produced by SAF emissions, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8217, https://doi.org/10.5194/egusphere-egu25-8217, 2025.
A CFD-microphysics coupling approach is presented for accurately predicting the formation and evolution of ice crystals originating from soot and volatile particles in the near-field of a turbofan engine. This method integrates an online Eulerian–Lagrangian coupling based on 2D axisymmetric unsteady Reynolds-Averaged Navier–Stokes equations to simulate exhaust plume dynamics. The framework incorporates tabulated chemistry (including 60 reactions, 22 reactive species, and 29 non-reactive species) and a detailed ice microphysics model. The model accounts for complex multicomponent interactions, including soot surface activation, condensation of organic vapors and sulfur species (H₂SO₄, SO₃), and the scavenging of sulfuric acid-water droplets by soot surfaces.
The analysis examines the effects of varying ambient temperatures, fuel sulfur content, and soot particle concentrations on ice crystal formation, which will be discussed in detail.
As a result, the figure compares the spatial distributions of plume particles, focusing on the effects of ambient temperature and fuel sulfur content. Specifically, it examines the spatial distribution of soot particles in three states: dried (black), activated (blue points), and frozen (cyan points). The comparison is presented for two scenarios:
a) ambient temperatures of 212 K and 218.8 K at a sulfur content of 700 ppm, and
b) sulfur contents of 700 ppm and 20 ppm at an ambient temperature of 218.8 K.
a)
b)
How to cite: Garnier, F., Cantin, S., and Chouak, M.: Influence of Fuel Sulfur Content and nvPM Emissions on Contrail Formation: A CFD-Microphysics Approach, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-13450, https://doi.org/10.5194/egusphere-egu25-13450, 2025.
Introducing hydrogen as an aviation fuel offers a promising pathway to significantly mitigate the climate impact of the aviation sector. While this transition demands substantial technological advancements and logistical transformations, hydrogen combustion produces zero CO₂ emissions. However, significant uncertainties remain regarding the non-CO₂ effects of hydrogen-powered aviation, particularly the impact of contrails cirrus. For conventional aircraft, contrail cirrus— the later stages of condensation trails—are estimated to exert an effective radiative forcing comparable to that of CO₂ emissions.
This study models contrail cirrus and their radiative forcing associated with hydrogen combustion. Using a theoretical framework for ice particle formation and a modified version of the CoCiP (Contrail Cirrus Prediction) model for contrail development and radiative forcing, we address key uncertainties specific to hydrogen combustion. These uncertainties include fuel burn, which depends on aircraft and engine design, and the characterization of the exhaust. Unlike conventional jet fuel combustion, which relies primarily on soot particles as condensation nuclei, hydrogen exhaust lacks soot, shifting the role of nucleation to entrained ambient aerosols and lubrication oil particles.
First, to address fuel burn variability, we model three tube-and-wing hydrogen-powered aircraft (short-, medium-, and long-range) with 2050 technology assumptions for realistic fuel flow estimates. Second, given the limited availability of empirical data of lubrication oil and the potential to optimize size and quantity in the exhaust through future engine designs, we evaluate the impact of lubrication oil particles on contrail cirrus by varying particle size distributions.
Our results show a consistent reduction in contrail cirrus radiative forcing across all lubrication oil particle size distributions when realistic hydrogen fuel flow is assumed. The largest reductions are observed in cases with larger mean particle radius and smaller variance. These findings provide insights into the potential for hydrogen-powered aviation to reduce the climate impact of contrail cirrus and highlight opportunities to steer engine design for further mitigation.
How to cite: Pettersson, S., Johansson, D., and Grönstedt, T.: Contrail Cirrus Climate Effects for Hydrogen-Propelled Aircraft, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6481, https://doi.org/10.5194/egusphere-egu25-6481, 2025.
The transition to climate-friendly aviation necessitates the development of new propulsion technologies to replace conventional kerosene combustion engines. Hydrogen (H₂) propulsion is widely regarded as a promising and environmentally sustainable alternative. A key aspect of creating climate-friendly aviation involves evaluating the climate impact of contrails, which significantly contribute to aviation’s non-CO₂ effects. This study examines the properties of contrails produced by H₂-powered aircraft, with a particular focus on comparing them to contrails generated by conventional kerosene combustion. Using high-resolution simulations performed with the EULAG-LCM model—a large-eddy simulation (LES) model with fully coupled particle-based ice microphysics—we analyze individual contrails throughout their entire lifecycle. This includes the interaction of young contrails with the downward moving wake vortices and their evolution into contrail-cirrus over several hours.
Previous simulations of early contrail evolution during the vortex phase and the subsequent contrail-cirrus transition have extensively explored variations in meteorological and aircraft-related parameters. However, these studies have been limited to contrails from kerosene combustion.
To assess the impact of H₂ propulsion on contrail evolution, we adjust two key input parameters: increasing the water vapor emission and varying the number of initial ice crystals. Additionally, we expand the atmospheric scenarios to include higher ambient temperatures, accounting for the fact that H₂ contrails can form in warmer conditions where ice crystal formation in kerosene plumes is not possible (assuming the same droplet characteristics in both cases).
We analyze H₂ contrail evolution in various atmospheric scenarios, finding that wake vortices cause significant ice crystal loss through adiabatic heating. This loss is less pronounced with fewer initial ice crystals but increases at ambient temperatures above 225 K. In the subsequent contrail-cirrus phase, we focus on the evolution of the contrail total extinction, which serves as a proxy for relative changes in the contrail’s radiative effect. Our results demonstrate that factors such as the initial ice crystal number, ambient temperature, and relative humidity strongly influence the contrail lifecycle, while increased water vapor emissions (immanent to H2 propulsion) have a secondary effect.
This work contributes to the collaborative effort of the German Aerospace Center (DLR) and Airbus in assessing the climate impact of H2 contrails.
How to cite: Lottermoser, A. and Unterstrasser, S.: High-resolution simulations of contrails from hydrogen-powered aircraft, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9035, https://doi.org/10.5194/egusphere-egu25-9035, 2025.
Contrail cirrus clouds contribute significantly to the climate impact of aviation. This impact depends non-linearly on the number of ice crystals formed in nascent contrails. For conventional kerosene combustion, ice crystals primarily form on soot particles emitted from the engine. However, in scenarios with reduced or no soot emissions (such as hydrogen combustion) other particles in the exhaust plume become relevant. Lubrication oil is one potential source of such particles.
Modern aircraft engines rely on lubrication systems to cool and lubricate rotating components such as bearings. When lubrication oil escapes into the environment—whether controlled or uncontrolled—it can become a source of volatile ultrafine particles. In the hot exhaust plume, the oil may evaporate and upon cooling of the plume nucleate new particles. Even if only a small amount of oil (on the order of a few milliliters per hour) forms new particles, the oil particle numbers can exceed the soot particle numbers of conventional engines if the resulting particles are only a few nanometers in size.
Although it is unclear to this point in how far this process occurs in the exhaust, this numerical study explores the potential role of oil particles in contrail ice crystal formation. By investigating many different scenarios, we study their activation behavior and importance compared to other ice-forming particles. The findings indicate that oil particles could substantially contribute to ice crystal formation in soot-poor or hydrogen combustion scenarios. While in-situ flight measurements are necessary to evaluate their actual formation, number, and size distribution, the study highlights the need to minimize oil particle emissions in aircraft exhaust as part of the transition to more sustainable aviation technologies.
How to cite: Zink, J., Unterstrasser, S., and Jurkat-Witschas, T.: The potential role of lubrication oil in contrail formation, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-3698, https://doi.org/10.5194/egusphere-egu25-3698, 2025.
Global aviation contrail climate forcing could match or exceed the forcing from aviation’s cumulative CO2 emissions. Aircraft engine exhaust contains various particles, including non-volatile particulate matter (nvPM), volatile particulate matter (vPM), and ambient aerosols. At cruise altitudes, these particles can activate to form water droplets if the relative humidity in the plume exceeds their activation threshold, where they subsequently freeze into contrail ice crystals. The initial number of contrail ice crystals is primarily driven by the nvPM in “soot-rich” conditions, where the nvPM number emissions index (EIn) exceeds a threshold of around 1014 kg-1; while vPM and ambient aerosols become more likely to activate to form contrail ice crystals under “soot-poor” conditions (nvPM EIn < ~1014 kg-1) (Yu et al., 2024). However, existing global contrail simulation workflows do not currently account for the potential activation of vPM, which may lead to an underestimation of the contrail climate forcing. This underestimation could likely be more significant for flights powered by: (i) cleaner lean-burn combustors, where their nvPM EIn at cruise is typically below 1012 kg-1; or (ii) sustainable aviation fuel (SAF), which can reduce the nvPM EIn by up to 70%.
An analytical model describing the microphysical pathway of contrail formation from nvPM and ambient aerosol particles was developed by Kärcher et al. (2015), which has since been extended to account for the potential activation of vPM in forming contrail ice crystals. Here, we aim to integrate this extended model into the contrail cirrus prediction model (CoCiP) to: (i) provide an updated estimate of the global annual mean contrail net radiative forcing (RF) for 2019; and (ii) quantify the simulated differences in contrail climate forcing between flights powered by conventional (rich-burn) and cleaner lean-burn combustors.
By accounting for vPM activation, our preliminary results estimates that the 2019 global contrail net RF could increase by up to 35%, depending on the assumed vPM properties (EIn and particle size distribution). On average, the contrail climate forcing from lean-burn combustors could be around 50% to 90% lower than that from conventional rich burn combustors. When compared with the simulation without vPM activation, the increase in contrail warming effects due to vPM activation in the exhaust of lean-burn combustors becomes significant only when the ambient temperature is at least 10 K below the Schmidt-Appleman criterion threshold temperature. Further work is ongoing to quantify the contrail mitigation potential from a fleetwide adoption of SAF and cleaner lean-burn engines.
References
Kärcher, B., Burkhardt, U., Bier, A., Bock, L., and Ford, I. J.: The microphysical pathway to contrail formation, Journal of Geophysical Research: Atmospheres, 120, 7893–7927, https://doi.org/10.1002/2015JD023491, 2015.
Yu, F., Kärcher, B., and Anderson, B. E.: Revisiting Contrail Ice Formation: Impact of Primary Soot Particle Sizes and Contribution of Volatile Particles, Environ Sci Technol, 58, 17650–17660, https://doi.org/10.1021/ACS.EST.4C04340, 2024.
How to cite: Teoh, R., Ponsonby, J., Shapiro, M., and Stettler, M.: The Role of vPM Activation in Global Contrail Climate Assessments and Mitigation Implications, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-17393, https://doi.org/10.5194/egusphere-egu25-17393, 2025.
Current estimates of the climate impacts of aviation condensation trails (contrails) are highly uncertain, primarily due to limited observational data and inconsistencies among different contrail models. However, contrails are thought to contribute substantially to the overall climate impacts of aviation, even at the lower end of the estimated uncertainty. One potential mitigation strategy is to reduce ice-forming emissions through advancements in fuel and engine technology. However, our current understanding of the sensitivities of contrail formation and radiative forcing to engine design variables and fuel properties is limited. Initial studies show that the early plume microphysics modeling (EPM) in contrail models such as the Aircraft Plume Chemistry, Emissions, and Microphysics Model (APCEMM) do not sufficiently capture the role of various emission species. These limitations include lack of representation of ice formation through homogeneous freezing of volatile aerosols, the effect of chemi-ions on aerosol coagulation, and a simplified treatment of nvPM and their activation.
To address these gaps, we aim to improve the existing EPM by including first principle-based modeling, supported by experimental results. In particular, the physics of condensation at the single-particle level is key to determining the transition towards ice crystals. This study investigates the role of nvPM activation via sulfates and organics, as well as the role of pore condensation and freezing, in contrail formation. The presence of sulfuric precursors can promote the activation of initially hydrophobic soot particles. Such particles have complex fractal shapes that include regions with high surface energy associated with open nano-and micro-pores, favoring the nucleation of critical water droplets. First results have shown that liquid fills the gaps between the primary particles of soot aggregates to form pendular rings which can develop even in a low saturation environment (Sr<1). The model used in the present study captures the realistic internal mixing of soot aggregates, from the activation up to heavy coating states, e.g., soot cores hosted within spherical droplets. The properties of the growing aerosols are measured throughout, including their size, density, and mass, as well as their optical signature, and will be communicated within APCEMM.
In addition, the effect of chemi-ions on aerosol coagulation will be considered. Implementing these microphysical considerations into the EPM, we can capture the soot-rich to soot-poor continuum of ice formation and test the impact of desulfurized fuel as well as low-soot emission indices on long term contrail evolution and the associated radiative forcing through APCEMM. With this work we hope to quantify the relative importance of various engine design parameters and fuel types to contrail formation, evolution, and, subsequently, climate impacts.
How to cite: Logrono, M., Jourdain, C., Boies, A., Prashanth, P., Speth, R., and Eastham, S.: Assessment of Exhaust Plume Microphysics for Quantification of Contrail Climate Impacts, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14010, https://doi.org/10.5194/egusphere-egu25-14010, 2025.
Contrails formed in aircraft exhaust plumes are a significant contributor to aviation’s climate impact; however, the physical processes driving their formation are not yet fully understood. This presentation focuses on advancing our understanding of non-equilibrium phase change phenomena, including homogeneous and heterogeneous condensation, liquid-to-solid transitions, and interphase momentum transfer, which are central to contrail formation.
The investigation is based on numerical methods of 3D RANS for non-ideal fluid flow and combined with well-established models in the field of steam turbines to describe the formation of a dispersed phase during phase change. Non-equilibrium thermodynamic principles are used to model nucleation and droplet growth, complemented by detailed representations of heterogeneous condensation and ice formation. The resulting approach is applied to simulate the flow behind an aircraft engine under upper tropospheric conditions. While capturing polydispersed size distributions of the dispersed phases and accounting for interphase momentum transfer, it enables a comprehensive investigation of contrail formation processes.
By assessing the influence of non-equilibrium effects on the validity of established approaches such as the Schmidt-Appleman Criterion, the presented method aims to bridge the gap between atmospheric-scale contrail models and detailed, small-scale physics of engine exhaust flows. In future work, these approaches could be used to explore how engine specifications, operational conditions, and fuel types shape the early stages of contrail formation.
How to cite: Tegethoff, K. and Smith, J. R.: Bridging the Scale Gap: Non-Equilibrium Phase Changes in Contrail Formation, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2784, https://doi.org/10.5194/egusphere-egu25-2784, 2025.
Contrails and contrail cirrus are the largest contributors of aviation radiative forcing, yet the exact quantification of their global impact remains far more uncertain compared to other sources, such as direct CO2 emissions. This uncertainty involves all phases of contrail lifetime –from formation until dilution in the free atmosphere. It is known for example that aircraft induce persistent contrails when flying in ice-supersaturated regions by providing condensation nuclei (soot particles or liquid aerosols) onto which ice nucleates and accumulates. These processes are strongly non-linear and also depend on the atmospheric conditions and engine setup among other parameters. Since it is not possible to explore the effects of all these parameters using detailed modeling such as 3D large-eddy simulations, low or mid-fidelity modeling approaches have been used in the literature with mixed success. In an effort to assist industry and modelers with design tools and flight trajectories definition, we developed an efficient computational method based on Reynolds Average Navier Stokes (RANS) simulations coupled to a stochastic model that captures the essence of jet turbulent mixing and the microphysical processes occurring in the plume. The method is validated for pure mixing using existing database of jet flow experiments and simulations, and it is then applied to contrail formation by activating simple ice microphysical models.
How to cite: Paoli, R. and Rigal, J.: Stochastic modeling of contrail formation, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14302, https://doi.org/10.5194/egusphere-egu25-14302, 2025.
Contrails have been identified as a principal contributor to aviation’s impact on the atmospheric radiative balance. However, considerable uncertainties remain regarding their effects, highlighting the need for deeper scientific understanding. Consequently, the development of reliable and validated contrail models is critical for accurate prediction and effective mitigation of their climate impact.
This study leverages ground-based camera imagery to identify and track early-stage contrails, providing benchmark data for a high-fidelity solver that simulates initial contrail formation. The solver employs a three-dimensional large-eddy simulation (LES) framework, incorporating an Eulerian–Lagrangian approach for two-phase compressible flow, enabling the simulation of the contrail's jet and vortex regimes over short timescales (<2 minutes). Images from Reuniwatt all-sky cameras capture a 5600 km² region at 30-second intervals, enabling observation of the vortex and initial dissipation regime.
Contrails are manually identified and labeled in the images, while flight trajectories are overlaid using ADS-B information. Atmospheric conditions are derived from reanalysis datasets at flight altitude, and aircraft/engine parameters are estimated from publicly available sources. These inputs are integrated into the simulations to replicate real-world conditions for each case.
By comparing the simulation results with observational data, this study aims to evaluate the reliability and applicability of the model, as well as to shed light on contrail formation mechanisms. Particular attention is given to scenarios where other theoretical approaches and lower-fidelity models have historically been less accurate.
How to cite: Quibén Figueroa, R., Ferreira, T., Gorlé, C., and Soler Arnedo, M.: Comparing high-fidelity LES of early contrail formation with ground-based images, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-17191, https://doi.org/10.5194/egusphere-egu25-17191, 2025.
Aviation’s environmental impact must be addressed in a multidisciplinary manner, further targeting improvements in CO2 emissions whilst also ensuring reductions in short-term non-CO2 radiative forcing, with particular focus on the largest contributor, aircraft contrails. Considering the challenges and cost associated with experimental measurements, to begin to formulate potential strategies to mitigate the impact of contrails, increased modelling fidelity and accuracy is required. Such work allows for the processes behind a contrail’s evolution to be better understood, whilst investigating key factors which dictate initial formation, particle properties, and climatic impact. From an engineering perspective, the key regions of interest are within the early regimes, covering contrail formation and early dynamics, where choices in aircraft and engine design can impact the initial contrail evolution.
To explore such effects, high fidelity RANS CFD with in-built contrail microphysics has been conducted on a fully featured aircraft geometry and its near-field wake. This allowed for accurate assessment of air vehicle performance, contrail formation, and aerodynamic interactions at cruise flight conditions. The CFD simulations incorporated a developed parametric aircraft model with realistic engine geometry to easily allow modifications in design to be studied and assessed in a multidisciplinary manner with respect to their environmental impact. To further increase the fidelity of the work, a detailed thermodynamic engine cycle model was coupled to the CFD boundary conditions and iterated upon throughout the simulations to ensure appropriate exhaust conditions for cruise flight were attained. Particle emissions at cruise were predicted by a machine learning model dependent on engine design and thrust setting. High level engine design choices, such as bypass ratio, were parametrised, with nacelle sizing requirements linked between the output of the engine model and CAD geometry to ensure installation effects and exhaust interactions were accurately captured, in addition to the required fuel burn and particle emissions. Simulation results from the early regime are intended to assess consistency with reduced fidelity model predictions, as well as to form a parametric input for longer term, global models.
Development of such models allows for aircraft/engine design exploration to be conducted to better understand pathways to potential mitigation of aviation’s environmental impact, inclusive of both CO2 emissions and contrails.
How to cite: Ramsay, J., Tristanto, I., Shahpar, S., and John, A.: Integration of mixed-fidelity aircraft/engine modelling to assess contrail mitigation strategies, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18681, https://doi.org/10.5194/egusphere-egu25-18681, 2025.
Contrails are ice clouds formed by both the aircraft emissions and the water content of the atmosphere. Under specific atmospheric conditions, contrails can persist for several hours. During this time, these human made clouds perturb the energy balance of the atmosphere. It has been shown in [1] that contrails are the main contribution of non CO2 radiative forcing due to aviation. There effective radiative forcing is estimated to be about twice the one from the CO2 emitted by the aircrafts; however, this value remains uncertain.
Contrails climatic impact is usually studied either by a dedicated parametrization in global climate model [2] or using a Gaussian model [3]. In both kinds of model, contrails are initialized once the dynamic of the aircraft can be neglected (about 7.5 min after the aircraft). Therefore, it is important to have the best parametrization of contrails at this stage of contrail’s life. To study contrails up to 7.5 minutes usually two different kinds of simulations are made. The first one covering the contrail formation (known as jet phase), and another one looking at the dissipation of the wing tip vortices (vortex and dissipation phases). Their formation is studied using RANS simulation [4] or with 0D models run on streamlines of a previous LES simulation of a single jet [5]. Then the results are injected in the vortex phase simulation ([6],[7]). When only a jet simulation is used, the wing tip vortices are initialized with two Lamb-Oseen vortices scaled based on the lift of the aircraft. However, a recent study [8] has shown some differences in terms of dilution between a simulation initialized based on a RANS solution and the analytical solution. This has be explained by 4 vortex instabilities which triggers shorter waves than the so called crow instabilities [9] as shown in [10].
In this study, we test the influence of the tail plan vortices on contrails characteristics assuming different tail plan vortices strength in order to see the dependency of the aircraft equilibrium on contrail.
[1] Lee et al. (2021). The contribution of global aviation to anthropogenic climate forcing for 2000 to 2018. Atmospheric environment
[2] Burkhardt et al. (2010). Global modeling of the contrail and contrail cirrus climate impact. Bulletin of the American Meteorological Society
[3] Schumann (2012). A contrail cirrus prediction model. Geoscientific Model Development
[4] Khou et al. (2015). Spatial simulation of contrail formation in near-field of commercial aircraft. Journal of Aircraft
[5] Bier et al. (2022). Box model trajectory studies of contrail formation using a particle-based cloud microphysics scheme. Atmospheric Chemistry and Physics
[6] Paoli et al. (2013). Effects of jet/vortex interaction on contrail formation in supersaturated conditions. Physics of Fluids
[7] Unterstrasser et al. (2014). Dimension of aircraft exhaust plumes at cruise conditions: effect of wake vortices. Atmospheric Chemistry and Physics
[8] Bouhafid et al. (2024). Combined Reynolds-averaged Navier-Stokes/Large-Eddy Simulations for an aircraft wake until dissipation regime. Aerospace Science and Technology
[9] Crow (1970). Stability theory for a pair of trailing vortices. AIAA journal
[10] Fabre et al. (2000). Stability of a four-vortex aircraft wake model. Physics of Fluids,
How to cite: Bonne, N. and Annunziata, R.: Influence of tail plan vortices on contrail vortex and dissipation phase, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11045, https://doi.org/10.5194/egusphere-egu25-11045, 2025.
Condensation trails (contrails) contribute significantly to the non-CO₂ climate impacts of aviation, with their effect estimated to be up to twice that of CO₂ emissions (Lee et al., 2021). Under specific atmospheric conditions, contrails can persist for several hours, potentially spanning tens of hours. To develop effective strategies for mitigating their climate impact, it is essential to investigate the processes that underlie their formation and evolution.
The formation and evolution of contrails are influenced by various factors, including the aircraft generating them (Unterstrasser et al., 2014). A recent study by Saulgeot et al. (2023) demonstrated that engine position affects the radiative properties of induced contrails. However, this analysis was based on a 2D assumption and initiated calculations at the onset of the vortex phase. Building on and extending this work, we present a 3D numerical study of contrail evolution during the vortex phase for different engine positions. Large-Eddy Simulations (LES) are initialized using Reynolds-Averaged Navier-Stokes (RANS) simulations conducted in the near-field of a realistic aircraft geometry, representative of a Boeing 777.
Three distinct engine positions are analyzed: one at 34% of the wingspan (typical of B-777 or A-320), another at 60% (outboard engine of a B-747), and a more academic configuration at 80%. The latter position aligns the propulsive jet with the wingtip vortex position, as predicted by elliptical wing loading theory, and represent the optimal configuration in the 2D study. Initialization involves extruding a slice of the RANS domain, obtained from prior simulations, onto the LES domain over a length corresponding to the wavelength of Crow instabilities, using the methodology developed by Bouhafid et al. (2024). This approach allows for the simulation of both contrail formation and its subsequent evolution over longer timescales. Microphysical processes, including soot-induced condensation, are modeled using an Eulerian approach (Khou et al., 2015). The simulations will extend up to 5 minutes after the effluent is ejected from the engine.
Simulation results reveal distinct aerodynamic behaviors, particularly in the lifetime of vortex dipoles, which are influenced by variations in jet proximity to wingtip vortices. These differences affect the resulting plumes, influencing both their spatial dispersion and the microphysical properties within them. As a result, the three configurations show variations in ice crystal radii and survival rates. These differences, in turn, impact the optical properties of the contrails, particularly their optical thickness.
How to cite: Annunziata, R., Bonne, N., Garnier, F., and Massot, M.: Numerical investigation of installation effects on condensation trail evolution during the vortex phase., EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16019, https://doi.org/10.5194/egusphere-egu25-16019, 2025.
Given the significant environmental impacts associated with global aviation, this sector must transition towards being more climate-friendly. Emissions from CO2 and NOx contribute substantially to climate change, while contrails also have a high negative impact. The establishment of formation flight configurations involving two or more passenger aircraft can support the reduction of the climate footprint, without the need for revolutionary technological improvements. By retrieving the energy generated from the wake vortex of the leading aircraft, subsequent aircraft experience reduced induced drag, thereby decreasing fuel consumption and emission (e.g., -5% CO2 and -15% NOx). As a consequence of atmospheric saturation effects, this approach also reduces the impact of contrails, resulting in an overall reduction in climate impact of approximately 25%.
The evolution of contrails depends on the dynamics of the wake vortices, as the aircraft exhaust and the resulting contrail ice crystals are captured within the wake vortex system and transported downwards. When flying in formation, the wake vortex system of the leading aircraft is affected by the interference with the wing and fuselage of the following aircraft. The complex interaction between the four wake vortex tubes requires a realistic modeling of the wake vortex dynamics behind a formation configuration. However, existing simulations have been limited to idealized scenarios.
To address this limitation, we develop a novel, refined and more realistic initialization method for our early contrail simulations. Firstly, we conduct RANS-LES simulations with two wings flying in formation, followed by the extraction of a velocity field downstream of the second wing. Subsequently, we initialize our early contrail simulations using this velocity field. This approach will be compared with previous analytical methods and with the contrail behavior of individual aircraft to quantify the potential for climate impact mitigation.
The work is performed as part of the EU project GEESE, which aims to demonstrate the operational feasibility of commercial formation flights over the North Atlantic and continental European airspace.
How to cite: Pauen, J., Unterstrasser, S., and Stephan, A.: Reducing Climate Impact through Formation Flying: A Refined Approach to Contrail Simulation and Wake Vortex Analysis, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-3653, https://doi.org/10.5194/egusphere-egu25-3653, 2025.
We present a brief outcome of our research with focus on recently developed persistence modeling framework referred to as AP3 “Accuracy Preserving Physics-based Persistence” model. The purpose of this framework is to predict the evolution of contrail to contrail cirrus and cirrus cloud over the course of >12hrs with preserved accuracy from the formation throughout its lifetime. The model captures nucleation of ice on particles through Gibbs-Free-Energy (GFE)-based classical nucleation theory (CNT) and accounts for particles coating and morphology on their nucleation propensity, which allows a physics-based representation of the dynamics of ice formation and growth post-sublimation. Other features of the model include, a DNS-based subgrid model for cloud-turbulence interaction, a source-based approach to account the impact of the cloud on surrounding atmospheric flow and a computationally efficient approach to track the cloud in earth-frame. AP3 is the learning machine for the PIML forecaster that is being developed as part of the ARPA-e CONFIRMMS program.
How to cite: Yazdani, M., Dean, T., Daw, E., and deBock, P.: A high-fidelity physics-based approach towards contrail and contrail cirrus persistence and longevity , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7019, https://doi.org/10.5194/egusphere-egu25-7019, 2025.
Observing contrail cirrus from satellites is challenging because of their low optical depth and large coverage. There is hence widespread reliance on contrail models to consider the periods in which contrails are too optically thin to be observable remotely. The lack of observational data for aged contrails means that contrail model validation relies on intercomparison, which is largely still missing in the literature. To address this, we compare CoCiP, the most used contrail model, to APCEMM, a 2D contrail model, under parametrized meteorological conditions. We show that APCEMM contrails persist for much longer than the equivalent CoCiP contrails, that the lifetime optical depth (a proxy for climate impact) in APCEMM is higher than that in CoCiP, and that the sensitivity of the lifetime optical depth to the relative humidity of the ice supersaturated layer is opposite between the models. These observations are explained by considering the contrail evolution in each model: CoCiP only simulates the fallstreak (the period in which the precipitation plume of the contrail has not reached the subsaturated layer), whereas APCEMM simulations exhibit behavior beyond this. Since post-fallstreak behavior has been seen in large eddy simulations and accounts for ~90 % of the APCEMM lifetime optical depth, our findings have significant implications for both global climate predictions and optimized contrail avoidance. Consequently, we call for the development of contrail models using new methodologies and for the increased collection of in situ observational data for aged contrails to robustly validate late lifetime behavior of contrail models.
How to cite: Akhtar Martínez, C., Eastham, S., and Jarrett, J.: Persistent contrails simulated in 0D models may experience premature evaporation compared to equivalent simulations in 2D models, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7191, https://doi.org/10.5194/egusphere-egu25-7191, 2025.
Contrail cirrus is estimated to be responsible for more than 50% of aviation induced climate forcing to date. However operational contrail avoidance is currently not possible due to the inability to predict exactly when and where a persistent contrail will form, and how that translates into radiative forcing. This research presents how to construct a high-accuracy physics-informed machine learning (PIML) models based on engine and weather variables to predict contrails formation parameters such as visibility, onset, and plumes’ optical depth as a function of distance from the aircraft. The approach is based on nonintrusive PIML model with low compute need at inference, making it ideal for onboard deployment. Based on a comprehensive sensitivity and feature importance study of the PIML model, this work demonstrates that spatial variation of plumes’ optical depth and as a result, the onset probability and location of contrails formation are only sensitive to a handful of engine and weather variables.
How to cite: Sarkar, S., Mondal, S., and Yazdani, M.: Physics-informed Machine Learning (PIML)-guided Contrails Formation Prediction, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7440, https://doi.org/10.5194/egusphere-egu25-7440, 2025.
Accurate simulation of contrail formation requires to capture the crucial nucleation of ice crystals in the jet phase and their evolution through the vortex phase. During these phases, the dynamics are largely dominated by the engine exhaust jets and the aircraft wake vortices, with turbulent fluctuations that drive the mixing of the hot gases with ambient air. The mixing influences the history of the thermodynamic quantities seen by all ice crystals and may therefore affect their final number concentration and size distribution after the demise of the aircraft wake.
A challenge in the simulation of spatially developing aircraft plumes lies in their extremely high aspect ratios, with a length of up to hundreds of kilometers and a cross-sectional dimension of hundreds of meters at most. To bring the computational expenses within a reasonable range, it is customary to simulate the jet and vortex phases separately. The former can be done in a space-developing paradigm. In contrast, the latter usually exploits a space-time analogy to limit the extent of the computational domain, allowing the plume to be aged in a time-developing manner. As a potential limitation of such a segregated approach, the initial condition of the vortex simulations often involves arbitrary assumptions on the velocity field and on the particle distribution. We propose to reconcile the two approaches using a technique to carefully transfer information between space- and time-developing paradigms while maintaining consistency in the momentum balance and particle distributions.
This study relies on Large Eddy Simulation performed with the Vortex Particle-Mesh method augmented with a simple ice microphysics model that tracks Lagrangian ice tracers and accounts for condensational growth and sublimation. We present the method itself together with the technique to transform space-developing results into a time-developing initial condition. We then consider a notional twin-engine aircraft with regular Jet fuel. The plume is first simulated in a space-developing manner in a domain of 100 wingspans in length. This case, considered the reference, is compared to time-developing simulations with various initial conditions, using either the presented technique or arbitrary assumptions. We assess the variability in ice crystal properties at the end of the vortex phase from these time-developing simulations and discuss the possible implications for the propagation of uncertainty into the contrail diffusion and dispersion phases.
How to cite: Caprace, D.-G., Duponcheel, M., and Chatelain, P.: Accurate Contrail Simulation In the Jet and Vortex Phases by Combining Space- and Time-Developing Paradigms, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-17034, https://doi.org/10.5194/egusphere-egu25-17034, 2025.
There is growing evidence suggesting that condensation trails (contrails) contribute to aviation-induced atmospheric warming at least as significantly as carbon dioxide emissions. Mitigating the warming effects of contrails requires the development of effective avoidance strategies, which in turn depend on accurate and computationally efficient contrail models. Contrails undergo multiple formation and evolutionary stages, beginning with their initial formation, progressing through a rapid growth phase, and culminating in their eventual dissipation or conversion into cirrus clouds. The long-term evolution of contrails—particularly their transformation into cirrus clouds—plays a critical role in defining their radiative forcing and climate impact. This stage of evolution is predominantly governed by advection-diffusion processes, coupled with particle-growth dynamics. We propose a novel contrail evolution model based on a coupled system of nonlinear advection-diffusion equations (ADE). This model integrates underexplored or previously neglected influences, including spatiotemporal wind variability, spatiotemporal and nonlinear diffusion coefficients accounting for diffusion limitation behavior, as well as significant ice-particle slip mechanisms. The proposed model is solved using an analytic discretization method, which outperforms classical numerical methods in terms of computational speed and accuracy. The model's performance is further compared against ground-based camera observations of contrails, providing an empirical basis for assessing its predictive capability. In addition, the model introduces several theoretical adjustable parameters, which can be calibrated using ground truth data to optimize its representation of advection-diffusion processes. This adaptability ensures that the model remains robust under varying atmospheric conditions and operational scenarios. By advancing our understanding of contrail dynamics and providing a computationally efficient solution framework, this work lays the foundation for more effective contrail avoidance strategies.
How to cite: Jafarimoghaddam, A., Soler, M., and Ortiz, I.: On the long-term propagation of contrails using a novel high-fidelity advection-diffusion model, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19765, https://doi.org/10.5194/egusphere-egu25-19765, 2025.
Over the past few decades, research has increasingly revealed the significant impact of non-CO2 emissions from aviation on global warming, with estimates suggesting they may account for as much or even more than the sector's entire CO2 footprint. While aviation produces various non-CO2 emissions, contrail cirrus is identified as one of the most significant contributor to aviation's climate impact. Whereas CO2 emissions linearly correlate to fuel consumption, this is not the case for contrail cirrus effects, making them more challenging to measure and mitigate. This highlights the importance of addressing contrail cirrus effects alongside CO2 and other emission reduction efforts in the aviation industry's pursuit of climate neutrality.
Here, we present first insights from the 100-flights-trial, a contrail avoidance demo trial by the German Aerospace Center (DLR) and the aviation industry tasked by the German federal government. In this trial, aircraft were actively rerouted (pre-tactical) to avoid airspaces with potential warming contrail cirrus formation. Existing models and tools were used to integrate the planning and execution of contrail avoidance flights into the flight operations processes. The analysis presented utilizes real flight data from 25 contrail avoidance flights operated by TUIfly which is then further analyzed using a modelling workflow consisting of DLR’s Trajectory Calculation Module (TCM), the Contrail Cirrus Prediction (CoCiP) model from the open-source pycontrails library, and ECMWF ERA5 reanalysis data. By comparing the originally planned trajectory, the contrail-optimized planned trajectory and the actual flown flight trajectory for each flight, we are able to quantify the effects of mitigation on parameters such as flight time, fuel consumption and the radiation effect of contrails. The methods developed may also be used to investigate the potential of the mitigation strategy and the impact on operational aspects like delay and fuel consumption. In addition, feasibility is considered with regard to airspace restrictions, optional direct routings, but also bad weather. We demonstrate through the implementation of contrail avoidance strategies that there is potential to achieve substantial reductions in the climate impact of contrails at a relatively low cost with comparable flight times. In addition, the choice of climate metric is shown to have little influence on the evaluation of the flights.
How to cite: Kirschler, S., Piontek, D., Juchem, M., Lau, A., Nalianda, D., Schymura, L. B., Solzer, J., Todt, C., Widmaier, K., Zengerling, Z., and Voigt, C.: Operational feasibility of contrail avoidance by flight trajectory adaptation: first insights from the German 100-flights-trial, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16836, https://doi.org/10.5194/egusphere-egu25-16836, 2025.
Cirrus clouds play a crucial role in regulating Earth’s radiation balance, with human activities altering their coverage and thus exerting a positive radiative forcing on the climate system. Among these, condensation trails left by planes, known as contrails, can persist into contrail cirrus which are nearly indistinguishable from natural cirrus. Their forcing constitutes most of the non-CO2 impact of the aviation sector, but its quantification remains very uncertain. Adjustments to radiative forcing are particularly poorly known, with estimates from a single climate model, where adjustments in natural cirrus counteract more than half of the initial radiative forcing.
We quantify the climate adjustments that follow abrupt, global transformation of water vapour in ice-supersaturated regions (ISSRs) into cirrus clouds. Using a new method based on ensembles of simulations with the French LMDZ atmospheric general circulation model, we analyse atmospheric and surface climate responses over a four-day period. We quantify the time constants of the ice water response, and its modulation of the initial radiative forcing. Preliminary results suggest that adjustments counteract 70% of the initial forcing within 4 hours.
Working with an simulation ensemble allows us to quantify a statistically significant behaviour of the adjustments and their time constants. Our findings enhance our understanding of the impact of contrails on climate and hold important implications for future climate modelling and prediction.
How to cite: Juvin-Quarroz, J.: On Short-Term Climate Adjustments Following Abrupt Cirrus Cloud Formation from ISSR, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8923, https://doi.org/10.5194/egusphere-egu25-8923, 2025.
Condensation trails from aviation have been shown to have a significant contribution to the total radiative impact of civil aviation. Consequently, their observation and modelling is an active field of research, so is the design of strategies to reduce the climate impact of aviation by avoiding contrail formation. However, the radiative efficacy of contrails in warming the climate is not well understood and constrained. Only a handful of studies have provided estimates of this key quantity so far. To better understand the impact of contrails on the climate, we developped a new parameterisation of contrails, cirrus clouds and ice supersaturation in the ICOLMDZ atmospheric general circulation model. This parameterisation is evaluated by estimating the value of radiative forcing of linear contrails and contrails evolving in cirrus clouds.
ICOLMDZ is the global atmospheric component of the IPSL-CM Earth System Model, actively and historically involved in the CMIP exercises. The standard version of ICOLMDZ is found to poorly represent cirrus clouds, and does not simulate ice supersaturated regions, which is a prerequisite for the formation of contrails. These regions are thermodynamically unstable, thus their modelling required a substantial revamp of the current parameterisation of cirrus clouds, which assumes thermodynamic equilibrium at all times. A new subgrid parameterisation that allows for ice supersaturation in both clear and cloudy sky was developped and implemented in ICOLMDZ.
This new parameterisation has then been adapted to simulate the effect of contrails and is used to assess the radiative forcing of contrails for a typical year, and a comparison with other state-of-the-art parameterisations in global climate models has been made. It will be used to estimate the efficacy of contrails to warm the Earth, using an ensemble of weakly nudged climate simulations with and without contrails.
How to cite: Borella, A., Boucher, O., and Vignon, É.: Modelling the climate effects of aviation in the ICOLMDZ climate model: From parameterising cirrus clouds and ice supersaturated regions to quantifying the radiative impact of contrails, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8888, https://doi.org/10.5194/egusphere-egu25-8888, 2025.
Contrails affect the radiative balance of the Earth climate (Lee et al., 2021). The representation of contrails characteristics and evolution into climate model remains highly challenging due to the complexity of the microphysical and chemical processes involved into the formation of contrails. The high sensitivity of contrails Radiative Forcing (RF) to the contrails morphology and composition in terms of ice crystal shape, number and size as well as surface temperature and albedo leads to major uncertainty when the RF of contrails is evaluated. In this paper, contrails RF has been modelled using the CEDRE-ASTRE Monte Carlo solver (Tessé and Lamet, 2011) for 1D and 2D idealized representations of a contrail in an atmospheric column (0 - 120 km). The role of the microphysical contrail characteristics have been evaluated using a multiple run sensitivity analysis to key parameters in the determination of contrails RF such as ice crystal size, ice water content, surface albedo and emissivity. A critical analysis of the results is made with comparable studies using different codes (Wolf et al., 2023) and will be detailed in the presentation.
References
Lee, D.S., Fahey, D.W., Skowron, A., Allen, M.R., Burkhardt, U., Chen, Q., Doherty, S.J., Freeman, S., Forster, P.M., Fuglestvedt, J., Gettelman, A., De León, R.R., Lim, L.L., Lund, M.T., Millar, R.J., Owen, B.,Penner, J.E., Pitari, G., Prather, M.J., Sausen, R., Wilcox, L.J., The contribution of global aviation to anthropogenic climate forcing for 2000 to 2018, Atmospheric Environment, 2021, 244.
Tessé L. and Lamet J.-M., Radiative Transfer Modeling Developed at ONERA for Numerical Simulations of Reactive Flows, AerospaceLab, ed. 2, https://aerospacelab.onera.fr/en/Radiative-Transfer-Modeling-Developed, 2011.
Wolf, K., Bellouin, N., and Boucher, O.: Sensitivity of cirrus and contrail radiative effect on cloud microphysical and environmental parameters, Atmos. Chem. Phys., 23, 14003–14037, https://doi.org/10.5194/acp-23-14003-2023, 2023.
How to cite: Terrenoire, E., Roch, M., Lamet, J.-M., and Tessé, L.: 1D/2D radiative forcing modelling of a contrail using a Monte-Carlo approach, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11650, https://doi.org/10.5194/egusphere-egu25-11650, 2025.
Contrail cirrus is estimated to be responsible for the largest and the most uncertain aviation effective radiative forcing (ERF) term. With the aviation sector’s commitment to reach net-zero emissions by 2050, there is a stringent need to better understand and constrain this term. A key challenge in reducing its associated uncertainty comes from the very limited number of climate models able to simulate contrail cirrus.
In this work we present results from two new contrail cirrus parameterisations for the UK Met Office Unified Model (UM), one based on the existing contrail scheme within the Community Atmosphere Model (CAM) and the other based on the prognostic contrail scheme developed for the ECHAM model. We find substantial differences in the simulated contrail coverage (up to a factor of 3) and radiative forcing (up to a factor of 8) caused by model differences in ice supersaturation and cloud microphysics schemes, together with existing uncertainty in contrail cirrus optical depth. Using the CAM model, we also quantify the change in the contrail cirrus climate impact due to switching to alternative fuels, such as sustainable aviation fuel (SAF), liquid hydrogen, and fuel cells. We find that the use of liquid hydrogen and fuel cells will likely lead to a substantial increase (up to 70%) in contrail cover compared to kerosene and SAF. However, our simulations indicate that despite this increase in coverage, the reduction in aerosol emissions associated with alternative fuels will lead to an overall reduction in contrail cirrus ERF.
We suggest that future work should focus on better constraining contrail cirrus optical properties (in particular for alternative fuels), and on improved representation of ice supersaturation and contrail microphysical processes in models.
How to cite: Rap, A., Zhang, W., Francis, T., Forster, P., and Feng, W.: Global climate modelling of contrails cirrus from current and alternative fuel aircraft, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9027, https://doi.org/10.5194/egusphere-egu25-9027, 2025.
Aviation currently contributes approximately 3.5% to the anthropogenic effective radiative forcing (ERF) on climate, with contrail cirrus being the largest contributor, accounting for twice the impact of aviation CO2 emissions. However, the latest assessment of aviation's climate impact highlights significant uncertainty of around 70% in contrail cirrus ERF estimates due to process-related uncertainties. Recent research also highlights the critical role of cloud microphysical schemes in representing contrail microphysical and optical properties in climate models.
In this study, we implement a contrail parameterisation in the double-moment cloud microphysics scheme, Cloud AeroSol Interacting Microphysics (CASIM), within the UK Met Office Unified Model (UM). This enables the UM to represent the high number concentration of young contrails, which is critical for the simulation of contrail cirrus evolution and climate impacts. We use a contrail cluster model experiment to evaluate the simulated contrail cirrus evolution, demonstrating that the CASIM modelled changes in several key contrail characteristics are consistent with previous modelling and observation studies. Our analysis indicates that contrails retain a high ice crystal number concentration for a several hours, while contrail ice water content increases during the early stage of the lifecycle before gradually decreasing. In addition, as the contrail cluster descends due to sedimentation, there is an increase in both contrail ice number concentration and water content below flight levels.
We also perform a series of regional simulations over a European domain (i.e. around 35°N-58° N and 10°W-22°E) using the AEDT air traffic inventory. We find that the regional mean contrail cirrus ERF over Europe simulated in our model compares well with estimates from other climate models. Our study highlights the critical role of using a double-moment cloud microphysics scheme when simulating contrails in global climate models. In contrast, results using the UM with a single moment cloud microphysics scheme fails to capture the high ice particle number concentration in young contrails, resulting in unrealistic ERF estimates. Future work with CASIM-UM should focus on estimating contrail cirrus ERF over other regions with high air traffic to provide a more comprehensive understanding of aviation climate impact. In addition, future work should also investigate how the use of alternative fuels affects ice crystal number concentrations, contrail lifetime, microphysical and optical properties.
How to cite: Zhang, W., Field, P., Forster, P., and Rap, A.: Modelling contrail cirrus using a double-moment cloud microphysics scheme in the UK Met Office Unified Model, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11993, https://doi.org/10.5194/egusphere-egu25-11993, 2025.
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.
[1] David S. Lee, David W. Fahey, Piers M. Forster, Peter J. Newton, Ron C. N. Wit, Ling L. Lim, Bethan Owen, and Robert
Sausen. Aviation and global climate change in the 21st century. Atmospheric Environment, 43(22):3520–3537, July 2009.
[2] Roger Teoh, Zebediah Engberg, Ulrich Schumann, Christiane Voigt, Marc Shapiro, Susanne Rohs, and Marc Stettler.
Global aviation contrail climate effects from 2019 to 2021. EGUsphere, 2023:1–32, 2023.
[3] Irene Ortiz, Ermioni Dimitropoulou, Pierre de Buyl, Nicolas Clerbaux, Javier García-Heras, Amin Jafarimoghaddam,
Hugues Brenot, Jeroen van Gent, Klaus Sievers, Evelyn Otero, Parthiban Loganathan, and Manuel Soler. Satellite-Based
Quantification of Contrail Radiative Forcing over Europe: A Two-Week Analysis of Aviation-Induced Climate Effects,
November 2024. arXiv:2409.10166 [physics].
[4] U. Schumann. A contrail cirrus prediction model. Geoscientific Model Development, 5(3):543–580, May 2012. Publisher:
Copernicus GmbH.
How to cite: Ortiz, I., Simorgh, A., García-Heras, J., Dimitropoulou, E., De Buyl, P., Clerbaux, N., and Soler, M.: Assessing Contrail Radiative Effects: A Comparison of MTG Satellite Detections and Physics-Based Simulations, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19879, https://doi.org/10.5194/egusphere-egu25-19879, 2025.
The development of effective contrail warming mitigation strategies requires the ability to accurately model contrail formation. This is a challenging problem for a number of reasons, including high uncertainty in the humidity data which is a key component of such models. Observational datasets can be used to constrain and improve contrail formation models. Here we present an analysis of existing contrail models on the task of predicting whether a contrail will be observed in a collection of observational datasets (collectively termed 'ContrailBench'). The observational datasets include one based on Ref [1] using automated contrail detections from the GOES-16 satellite and an automated contrail attribution algorithm, another based on Ref [2] which detects contrails using GOES-16 and uses knowledge of the altitude from LIDAR measurements to attribute them to flights, and a third dataset based on Global Meteor Network ground-based camera imagery [3] with automated contrail detection and high-confidence attribution to the flights that formed them. Different downstream applications require different properties from contrail models, so we evaluate the contrail models based on their performance in both ‘high-recall’ mode (which prioritizes identifying all the flights which make contrails) as well as in ‘high-precision’ mode (which prioritizes minimizing the number of flights incorrectly predicted as forming a contrail). We find that models using raw ERA5 weather reanalysis data perform poorly on all metrics, but the use of machine learning to correct the weather data can lead to improvement.
[1] A. Sarna et al, “Benchmarking and improving algorithms for attributing satellite-observed contrails to flights”, https://doi.org/10.5194/egusphere-2024-3664
[2] V. Meijer, thesis, “Satellite-based Analysis and Forecast Evaluation of Aviation Contrails”
[3] D. Vida et al, “The Global Meteor Network – Methodology and first results” https://doi.org/10.1093/mnras/stab2008
How to cite: McCloskey, K., Meijer, V., Busquin, L., Busquin, J., Vida, D., Dean, T., and Geraedts, S.: ContrailBench: evaluating the performance of contrail models, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4596, https://doi.org/10.5194/egusphere-egu25-4596, 2025.
Navigational avoidance as a contrail mitigation strategy has the potential to reduce the climate impact of aviation by as much as half. The effective implementation of avoidance strategies requires forecasts of the state of the upper troposphere and lower stratosphere that are stable (consistent across a range of lead times) and accurate (true to reality). However, the optimal criteria for evaluating whether a contrail forecasting system is sufficiently stable and accurate remain unclear. Here, we argue that forecast stability is best evaluated holistically by asking whether estimated decreases in contrail warming, for a given set of flight trajectories and deviations, are consistent across forecasts with different lead times. We use real-world flight trajectories taken from operational ADS-B datasets and deviations generated using aircraft performance models with a contrail-aware trajectory optimization routine to evaluate the stability of contrail predictions based on ECMWF IFS HRES forecasts. We find a high degree of stability with contrail warming reduced by over 80% even with lead times as long as 48 hours, sufficient to enable pre-tactical contrail avoidance at the flight planning stage. Finally, we show that we obtain large reductions in contrail warming despite frequent pointwise differences in the locations of ice supersaturated regions across forecast cycles because forecasts agree on the broad regions where ice supersaturation occurs.
How to cite: Dean, T., Abbot, T., Engberg, Z., Masson, N., Teoh, R., Stettler, M., and Shapiro, M.: Evaluating Forecasts for Navigational Contrail Avoidance, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7230, https://doi.org/10.5194/egusphere-egu25-7230, 2025.
Contrails are estimated to have one of the largest contributions to aviation’s effective radiative forcing [1]. Fortunately, potential operational and technical measures have been identified to mitigate contrail induced warming. A promising mitigation strategy is to avoid persistent contrail formation through optimised flight trajectories. However, employing such a strategy is currently hampered by the large uncertainties involved in predictions for persistent contrail formation. This uncertainty introduces a risk of unsuccessful or unnecessary detours, resulting in needless extra emissions and fuel burn. Policymakers need to know the magnitude of this risk to carry out mitigation strategies effectively. Yet, estimates of persistent contrail formation are often provided in a deterministic manner, lacking quantifications of uncertainty. Furthermore, earlier studies that do quantify uncertainty often introduce an assumed or simplified uncertainty or propagate a limited scope of uncertainty sources (e.g., [2]). Therefore, instead of simple binary outputs (persistent/non-persistent), this work constructs an approach to quantify the probability of persistent contrail formation for flight waypoints, regarding a wider scope of realistically quantified uncertainty sources than done before.
To quantify the uncertainty of meteorological parameters, we employ the method of Bayesian Model Averaging (BMA) [3]. Using BMA, modelled weather data from ECMWF Reanalysis v5 (ERA5) is calibrated with data from the IAGOS measurement campaign [4]. The calibration process overcomes the bias and under dispersiveness of ERA5 and constructs probability distributions for humidity, temperature and wind. Relevant uncertainties related to the aircraft and its performance are quantified using the variance of these parameters among different estimates of their value.
The obtained uncertainties are propagated to obtain the probability that the condition for contrail formation, the Schmidt-Appleman criterion, is satisfied for waypoints along a flight. Further in the contrail development, we assess the chance that a formed contrail survives the wake downwash phase, to quantify the likeliness of contrail persistence. Moreover, we produce a probabilistic result for potential contrail cirrus coverage (PCC), a parameter representing the fractional area of a grid box in which contrail cirrus can persist once they have been formed. The approach is applied to real flights over the North Atlantic in 2019, from the perspective of an airliner when planning flights for persistent contrail avoidance. We intend to verify the hypothesis that the presented approach reduces the risk of failed avoidance of persistent contrail formation with respect to an approach using binary estimates of contrail persistence.
[1] Lee, D.S. et al. (2021) ‘The contribution of global aviation to anthropogenic climate forcing for 2000 to 2018’, Atmospheric Environment, 244, p. 117834.
[2] Platt, J.C. et al. (2024) ‘The effect of uncertainty in humidity and model parameters on the prediction of contrail energy forcing’, Environmental Research Communications, 6(9), p. 095015.
[3] Raftery, Adrian E., et al. (2005) ‘Using Bayesian model averaging to calibrate forecast ensembles’, Monthly weather review, 133.5, p. 1155-1174.
[4] Petzold, A. et al. (2015) ‘Global-scale atmosphere monitoring by in-service aircraft – current achievements and future prospects of the European Research Infrastructure IAGOS’, Tellus B: Chemical and Physical Meteorology, 67(1), p. 28452.
How to cite: Kruin, W., Faleiros, D., Yin, F., and Grewe, V.: Probability of Successful Avoidance of Persistent Contrails, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16151, https://doi.org/10.5194/egusphere-egu25-16151, 2025.
How to cite: Gryspeerdt, E., Bennett, L., Driver, O. G. A., Fearn, A., Neely III, R. R., Stettler, M. E. J., Walden, C. J., and Walker, D.: The Contrail OBservations And Lifecycle Tracking (COBALT) project - Observations and initial results, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-20111, https://doi.org/10.5194/egusphere-egu25-20111, 2025.
Aircraft contrails are a significant contributor to aviation-induced climate effects, but attributing individual contrails to specific aircraft remains a challenge, especially when relying solely on satellite data. Satellite imagery offers extensive coverage but is limited by temporal and effective spatial resolution due to the large imaging distance. We propose a methodology that integrates freely available ground-based webcams, with ADS-B flight data to detect and attribute contrails to specific flights.
We project flight trajectories from ADS-B data with latitude-longitude-altitude coordinates into the ground camera frame of reference using camera extrinsics pre-calculated from geographic points of reference. We then use a contrail segmentation method based on Canny edge detection and curve fitting to identify contrails in the frame of reference of the ground camera, capitalizing on the ground camera’s proximity and high framerate to attribute detected contrails to flights. Detected contrails can also be projected from ground camera space to satellite perspective, enabling the direct comparison between ground camera and satellite-based detection and attribution methods. With higher-accuracy ground-camera based attribution, we also enable the validation of more challenging satellite-based contrail attributions.
By leveraging the proximity of ground cameras for higher effective spatial resolution and their continuous capture for higher temporal resolution, our system addresses key limitations of satellite data. Our framework lays the groundwork for improved understanding of contrail creation, lifecycle, persistence, and more reliable monitoring of aviation-induced climate impacts. This method has the potential to enhance and validate operational contrail monitoring and avoidance and improve the integration of ground-based observations with satellite-based methods.
How to cite: DuTell, V., Kigotho, O., Borad, S., Pless, R., Prakash, P., Waitz, I., and Freeman, B.: Ground Cameras with ADS-B Data for High-Resolution Contrail Detection & Attribution , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-13300, https://doi.org/10.5194/egusphere-egu25-13300, 2025.
Cloud formation, especially cirrus type, is affected also by the human activities such is aviation, which emits condensation trails, called contrails. Contrails form and persist under specific environmental conditions. Their formation is conditioned by the fulfillment of the Schmidt–Appleman, and later on their persistence is guaranteed over the ice supersaturated regions. These conditions, use the air temperature and relative humidity related to water and ice as criteria for their formation and persistence. These criteria depend, not only on the meteorological conditions but also on the aircraft specification, their fuel type, engine efficiency, etc.
One interesting topic of the contrail effects is the investigation of their contribution on the formation of the cirrus clouds. The formation of the cirrus clouds requires generally significantly higher relative humidity then the contrail persistence conditions. In this way, the investigation of the persistent contrails with relative humidity lower than cirrus clouds need to be formed, enable to have insight over the contribution of the contrails on the cirrus formation.
Currently, we have a 20-year database that allows us to do statistics but at night, which requires us to develop methods for differentiating clouds and contrails. Lidar backscattering profiles are collocated with system ADS-B data of the flight overpassing the Observatory of Haute-Provence in France. Detailed information about the flight routes and meteorological conditions, associated with the contrail properties have been analyzed statistically and case by case.
Here, statistics of the contrail formation and persistence conditions over the site is presented. The events have been classified into five cases; persistent, non-persistent, potential, uncertain and no contrails. The geometrical and optical properties of the contrails, as well as related meteorological variables provided by ERA5, are grouped according to this classification. The principal factor analyses on the contrail parameters is performed and their outputs have been clustered to identify better the main features of the most important parameters.
In addition to these statistics, some special cases of the contrail events have been analysed. The information provided by system ADS-B collocated with the lidar vertical-resolved profiles identify and follow up the evolution of the contrails over the site. Their mean altitude, geometrical thickness, spatial orientation, timespan, width, optical depth and their persistency have been analysed in thoroughly. To have adequate determination and discrimination of the contrail spots, sensitivity analyses have been performed for the backscattering ratio, and their spatial and temporal distances between their neighbors. In short, complementary analyses, using statistics and cases studies, is performed to clarify the features of the contrail main properties.
How to cite: Mandija, F., Keckhut, P., Alraddawi, D., and Irbah, A.: Contrail detection at nighttime combining lidar, meteorological and system ADS-B data , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19851, https://doi.org/10.5194/egusphere-egu25-19851, 2025.
Aviation affects the Earth’s energy balance through both non-CO2 effects and exhaust gases and soot emissions. One such effect is the formation of contrails, which can alter the climate impact of cirrus clouds and their optical and microphysical properties. In this study, embedded contrails were detected during active remote sensing observations with the German research aircraft HALO. Using observations during ML-CIRRUS, it is found that embedded contrails can be identified in WALES lidar measurements through particle backscatter coefficients larger than 4 Mm−1 sr−1 and particle linear depolarization ratios (PLDR) below 30% and 43% for clouds with low and high mean PLDR, respectively. The thus identified contrail-affected lidar and lidar-radar measurements during ML-CIRRUS and other HALO campaigns will be used to assess the impact of contrails that form in already existing cirrus clouds on the optical and microphysical properties of those clouds, and in how far potential affects might also be detected in spaceborne lidar observations.
How to cite: Soleimanpour, M., Tesche, M., and Groß, S.: Occurrence of embedded contrails in cirrus clouds observed with the HALO research aircraft, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-17834, https://doi.org/10.5194/egusphere-egu25-17834, 2025.
Contrail cirrus is estimated to be the largest contributor to global effective radiative forcing from aviation, surpassing even aviation CO2 emissions in their impact. One promising mitigation strategy is contrail avoidance by rerouting flights to avoid regions where warming contrails can persist. These regions are forecast with numerical contrail models fed with weather prediction model output. Satellite imagery presents a good opportunity to evaluate both the models and the success of the mitigation strategy.
An automatic contrail detection algorithm was implemented by Mannstein et al. (1999) for a polar orbiting satellite with high spatial resolution (≈ 1 km and used two thermal channels in the atmospheric window). Since then, it has been adapted to the Meteosat Second Generation (MSG) satellite because geostationary satellites have the big advantage of high temporal coverage of a large area. However, its lower spatial resolution (≥ 3 km) is a challenge for contrail detection. In recent years AI algorithms have been presented for the American geostationary GOES-R/S satellites (spatial resolution ≥ 2 km). In this study, a new improved contrail detection algorithm for MSG is proposed based on image processing.
To establish a new detection algorithm a labeled dataset was compiled. This labeled dataset contains 140 MSG images with data from the years 2013-2018 and 2023-2024. This data volume is very suitable to develop and evaluate an algorithm with a classical approach, would however not be sufficient to train an AI based algorithm. The data covers the whole MSG disk with a wide distribution of satellite viewing angles, cloud cover, number of contrails in the image and other properties. Each image was labeled by three individuals, and a common contrail mask was established as the consensus of the labelers. Based on this dataset, a new detection algorithm was developed. Making use of the spectral information of MSG, an image is created as input for the algorithm where contrail visibility is enhanced. The algorithm takes advantage of several new techniques compared to Mannstein et al. (1999). In addition to the contrail mask, uncertainty information is provided.
This new algorithm for contrail detection in MSG images demonstrates superior performance compared to the previous algorithm for MSG based on the Mannstein approach with a probability of detection higher than 70%. The contrail detection algorithm can now be employed for generating datasets to evaluate contrail models as well as to assess the success of contrail mitigation strategies such as flight path alteration. Thanks to this classical image processing approach, in the future the algorithm can be adapted to other satellites like Meteosat Third Generation.
How to cite: Santos Gabriel, V., Bugliaro, L., and Voigt, C.: A novel Contrail Detection Algorithm for the Meteosat Second Generation satellite, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9076, https://doi.org/10.5194/egusphere-egu25-9076, 2025.
Cloud formation can also result from human activity, such as aircraft condensation trails, or contrails. They are created by the release of water vapor and soot from aircraft. Contrails can then change shape rapidly after forming, and then persist in the atmosphere for varying lengths of time. They will persist in the atmosphere if the air is super-saturated with ice, i.e. when the height of aircraft is in the upper troposphere. They can then evolve into cirrus clouds if the thermodynamic conditions of the atmosphere are favourable. These cloud-like contrails will therefore have environmental consequences that need to be understood to be included in climate models as non-CO2 contributions. These are the main motivations that led us to the establishment of ground facilities at the Haute Provence Observatory (OHP south of France) to observe and study condensation trails. They are mainly composed of a Lidar, radiosondes and two sets of fisheye cameras recording hemispherical images of the sky in the visible and thermal infrared for nighttime observations. The Global Horizontal Irradiance (GHI) of the Sun and some meteorological data on ground are also recorded together with the images. We will first describe in detail the instrumentation currently installed on the ground and operational for contrail monitoring. We will then present a case of a contrail recorded on March 21, 2024 at OHP and detail all the processing steps, from its detection to its analysis, including the identification of the aircraft trajectory in the images and the expansion of the contrail it leaves.
How to cite: Irbah, A., Keckhut, P., Alraddawi, D., Mandija, F., and Liandrat, O.: Ground-based installations at the Haute Provence Observatory (OHP) to monitoring and study condensation trails, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11372, https://doi.org/10.5194/egusphere-egu25-11372, 2025.
Condensation trails (contrails) are ice clouds formed at high altitudes as a result of water-vapour condensing and freezing on soot particles and sulphate aerosols which are present in the aircraft engine plumes (case of soot-rich combustion with kerosene [1]). Under favourable atmospheric conditions such as ice supersaturated regions, i.e., low temperatures and high humidities with respect to ice, these contrails can persist for up to several hours while covering large areas. The latter is especially important when considering the climate impacts of the aviation emissions as the radiative forcing from persistent contrails and contrail-cirrus is one of the major contributors [2].
Therefore, improving the understanding of the underlying physics of contrail is of utmost importance for the development of mitigation solutions. The process of formation and early evolution of the ice crystals occurs within the first few seconds which is often referred to as the jet phase. As such, Computational Fluid Dynamics (CFD) serves as an important tool in studying the near-field wake of the aircraft. In this study, we use a Reynolds-Averaged Navier Stokes (RANS) CFD solver, named FLUSEPA [3], to simulate the exhaust of the Common Research Model (CRM) [4] engine up to 500 m behind the engine (focusing on the mixing of the plume and not the ice crystal formation). FLUSEPA is a solver developed by Ariane Group for launcher propulsion. Furthermore, we consider an engine powered by hydrogen combustion consequently emitting about 2.6 times more water-vapour mass than a kerosene-powered engine. Note that for a hydrogen-powered engine, depending on the design choices, ice crystals would most likely form on a combination of ambient aerosols and/or soluble NOx particles.
The RANS solver is used to simulate an idealised configuration of an isolated engine. This allows us to validate the dynamics of the jet in the axial direction. We briefly describe the methodologies used so as to obtain the plume’s dilution as a function of the axial position which can then be used by an offline microphysics model to simulate ice crystal formation. Finally, we vary physical and numerical parameters relevant to contrail formation to identify their role on the dilution factor.
References
[1] Yu, Fangqun, et al. "Revisiting contrail ice formation: Impact of primary soot particle sizes and contribution of volatile particles." Environmental Science & Technology 58.40 (2024): 17650-17660.
[2] Lee, David S., et al. "The contribution of global aviation to anthropogenic climate forcing for 2000 to 2018." Atmospheric environment 244 (2021): 117834.
[3] Pont, Grégoire, and Pierre Brenner. "High order finite volume scheme and conservative grid overlapping technique for complex industrial applications." Finite Volumes for Complex Applications VIII-Hyperbolic, Elliptic and Parabolic Problems: FVCA 8, Lille, France, June 2017 8. Springer International Publishing, 2017.
[4] Vassberg, John, et al. "Development of a common research model for applied CFD validation studies." 26th AIAA applied aerodynamics conference. 2008.
How to cite: Purseed, J., Pont, G., Romeo, J.-P., Huber, J., Arsicaud, L., Mackay, C., and Renard, C.: RANS simulations for contrail formation modelling, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9774, https://doi.org/10.5194/egusphere-egu25-9774, 2025.
The steady increase in global air traffic demand has led to a corresponding rise in contrail radiative forcing, contributing significantly to effective radiative forcing (ERF). Contrails, formed when hot exhaust gases from jet engines mix with cold, humid ambient air, have a warming effect that can surpass the CO₂ emissions of aviation in the short term. While contrail mitigation strategies often focus on adjustments to cruise altitudes and flight trajectories, less attention has been given to the impact of climb and descent phases, and particularly their effects on cruise phases for short- and medium-range flights. This study explores the contrail mitigation potential of these flight phases, providing a comprehensive analysis of their contribution to contrail formation, and associated operating costs.
Contrail persistence depends on atmospheric conditions within ice-supersaturated regions (ISSRs), primarily occurring at typical cruising altitudes. However, the dynamics of the initial climb and final descent phases should only occasionally allow for contrails to form, and much less for persistence to occur, primarily due to higher temperatures at low altitudes. When transitioning through vertical layers of ISSRs, some contrails may however still form, though a quantification of this phenomenon is lacking. Thus, by leveraging simulations conducted with an air traffic simulator embedded in a climate-chemistry model (EMAC/AirTraf), this study investigates contrail formation during these phases, narrowing this gap. By incorporating these overlooked flight segments, we aim to provide a more accurate estimate of contrail prevalence.
A critical aspect of the analysis involves quantifying the impact of climb and descent phases on contrail length and operating costs. By grouping simulations based on flight length for a set of European flights, this study elucidates differences in contrail distances and cost estimated using fuel consumption. In order to investigate this, the flights are first analysed using an airport to airport trajectory, optimised using different objectives such as contrail distance minimum, fuel optimal, and multi-objective (fuel-contrail). For airport to airport, it assumes that these flights entirely occur at cruise altitude. The next step uses more realistic trajectories, considering a cruise phase bounded by climbing and descending phases, using the same optimisation options. The direct impact of climb and descent in terms of contrail distance is observed from the difference between the original trajectory (airport-airport) and the cruise only trajectory. Next using the cruise only trajectory determined with the standard entry/exit points, also known as standard instrument departures (SID) and standard instrument arrivals (STAR), together with the separate impact of ascent/descent, the overall climate impact reduction potential can be determined for a more realistic flight path, using algorithmic climate change functions (ACCF).
By applying this method, we expect to identify the potential contribution of climb and descend to the contrail climate impact for a given flight. By extension, this would indicate the relevance of climb/descent phases in contrail mitigation potential studies, regardless of chosen optimiser, and moreover, the differences arising in the mitigation potential as a function of flight length.
How to cite: Stefanidi, A., Yin, F., and Grewe, V.: Assessing Contrail Mitigation Potential Through Initial Climb and Final Descent Phase Analysis: A Comparison of Short- and Medium-Range Flights Within Europe, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9779, https://doi.org/10.5194/egusphere-egu25-9779, 2025.
Contrail cirrus represents the most significant warming component within the total aviation impact on climate, suspected to exceed even the effects of aviation CO2 emissions. It remains to be shown that regulating hydrogen and sulfur content in aviation kerosene could help to reduce the climate impact from CO2 and from contrails, in order to allow for a science-based jet fuel standardization. Hence, this study conducts a model-based scenario analysis of the climate impact of the European fleet in 2019, exploring different levels of aromatic and sulfur reductions in fossil fuel-based kerosene as short-term mitigation measures.
Using the Lagrangian plume model CoCiP within the open-source pycontrails package, we simulate contrail properties and energy forcing (EF) for a reference fleet using Jet-A1 fuel (13.8% hydrogen content) over Europe in 2019. For scenarios with increased hydrogen content (13.8%–15.4%, in 0.2% increments), reductions in non-volatile particulate matter (nvPM) emissions and changes in contrail properties—such as initial ice particle number, persistent contrail formation, age, optical depth, contrail coverage, and EF—are quantified. In parallel, sulfur content scenarios—including high and ultralow levels with increased and reduced soot activation fractions, as well as zero sulfur—are analyzed, to estimate the impact of sulfur-mediated elevated or reduced activation of aerosol into water droplets.
The reference simulations compare well to previous studies. Furthermore, results show that increasing hydrogen content from 13.8% to 15.2% (the theoretical maximum) enhances the potential for persistent contrail formation from 13% by 6%, but reduces nvPM emission index from 1.22 x 1015 kg-1 by 61%, contrail age from 2.37 h by 20%, contrail optical depth from 0.12 by 24%, and contrail cirrus coverage from 0.67% by 34%. This leads to a reduction in total EF by up to by 52%. The high sulfur scenario increases contrail EF by up to 10%, while the ultralow scenario reduces EF by up to 14%. The simulation of the zero-sulfur content scenario represents the potential lower limit and serves as a pre-study for hydrogen combustion. These findings, part of the European Fuel Standard project by the European Union Aviation Safety Agency, demonstrate how improving fuel composition can mitigate aviation climate impact. These results highlight the potential of hydroprocessed and ultra-low sulfur kerosene as near-term solutions, providing actionable insights and implications for the development of aviation fuel standardization.
How to cite: Wang, Z., Marsing, A., Voigt, C., Piontek, D., Kirschler, S., Widmaier, K., and Bugliaro, L.: Modeling the impact of aviation fuel hydrogen and sulfur content on contrail properties: insights and implications, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4258, https://doi.org/10.5194/egusphere-egu25-4258, 2025.
Aviation emissions contribute to climate change, one of the key contributors being contrail cirrus clouds. The importance of this impact is strongly dependent on their properties .
A condensation trail - or contrail - is composed of ice crystals which form behind the aircraft engine exhaust at high altitudes when local weather conditions are favorable. The formation is also influenced by the engine technology and operating conditions, and by the fuel type. The contrail persists and evolves as long as it remains in an ice supersaturated region, a local atmospheric air mass characterized by a low temperature and a humidity level that is saturated versus ice. Only persistent contrails are considered as having a climate effect.
Hydrogen propulsion is considered as one promising technology to reduce aviation’s climate impact, in line with the European Green Deal and Clean Aviation Strategic Research and Innovation Agenda (SRIA). In this context, the EU-funded HYDEA project proposes a robust and efficient technology maturation plan for H2 propulsion.
The formation of contrail ice crystals in an aircraft plume is mainly driven by the interaction of three physical phenomena: the dynamics in the engine exhaust, chemical transformations of effluents and microphysical processes.
The main assumptions when moving from a kerosene to a H2 fueled propulsion system are that there will be no soot particles in the jet exhaust, and an increased water vapour emission compared to kerosene. New modelling chains are required to understand how, in this case, ice crystals are formed and they evolve.
The models under development will be presented along with the assumptions being made. In HYDEA Work Package 6, two H2 contrail models using complementary methods are under development, using the Common Research Model [1]. The ONERA model using the 3D model CEDRE for both jet and vortex phases simulation provides a high-fidelity engine and aeroplane representation. The DLR model uses a Lagrangian Cloud Module box model approach with particle-based microphysics providing a high-fidelity microphysical representation with a simplified geometry. This ingests jet exhaust CFD data provided by Airbus and GEAP. The latest scientific developments and assumptions being incorporated in the models are discussed.
[1] Development of a Common Research Model for Applied CFD Validation Studies: J. Vassberg, M. Dehaan, M. Rivers & R. Wahls. 26th AIAA Applied Aerodynamics Conference 2012, June 2012, Hawaii, United States. https://doi.org/10.2514/6.2008-6919.
How to cite: Mackay, C., Arsicaud, L., Purseed, J., Unterstrasser, S., Zink, J., Roszkiewicz, K., Iglewski, T., and Bonne, N.: HYDEA Project Work Package 6: Contrail modeling for hydrogen combustion., EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11011, https://doi.org/10.5194/egusphere-egu25-11011, 2025.
Sustainable aviation fuels (SAF) offer a promising pathway to mitigate the climate impacts of aviation by reducing contrail formation. The VOLCAN project utilises ONERA’s advanced 1D microphysical model MoMiE1, 2 (Modèle Microphysique pour Effluents) to assess SAF's effects on exhaust plumes and contrail characteristics across various fuel types and combustion modes. Written in FORTRAN, MoMiE offers exceptional computational efficiency and a robust set of libraries suitable for high-performance scientific computing. However, its rigidity can slow down development cycles and make the code less adaptable to the rapid iteration often required in research and development settings, such as in the testing of new types of sustainable aviation fuels. Currently, MoMiE supports the modelling of heterogeneous freezing on soot particles activated by sulfuric acid and organic species, homogeneous freezing of liquid sulphate and organic droplets, and the competition between these modes. Additional features include the representation of chemiionisation, Brownian coagulation, and the growth and sublimation of ice crystals. However, these processes are hardcoded into the code base, making it cumbersome to run a variety of experiments with supported species and difficult to expand to cover novel fuel scenarios.
To address these challenges, we discuss a modern, object-oriented, and modular Python-based approach tailored for emerging numerical modelling experiments of SAFs. We aim to retain the above functionality while providing a robust framework for future code development. Core components, including aerosol and molecular species distributions, scientific models (nucleation mechanisms), and thermodynamic calculations, are encapsulated within distinct Python classes, ensuring a clear separation of concerns and facilitating focused updates and development. The model objects are configured a priori with user-defined configuration files. These files specify molecular species relevant to specific fuel or burn scenarios, as well as different scientific models, nucleation schemes, experimental data sets etc., ensuring the code remains extensible without disrupting its foundational framework. In addition, all operational parameters and physical constants are externalised, making the code more flexible and encouraging maintainable, transparent coding practices. Python classes are instantiated dynamically during runtime, rather than being pre-defined at model start-up. This approach avoids unnecessary dependencies and ensures that objects are created only when needed, optimising memory usage and maintaining computational efficiency. We will explore preliminary results of quantitative scientific comparison with MoMiE in a few test cases and performance benchmarking.
The proposed development aims to replicate and extend the capabilities of 1D simulations in MoMiE, employing a design philosophy that supports scalability and adaptability. This approach aligns with the evolving scientific and operational demands of SAF research, enabling detailed and flexible modelling of complex microphysical processes.
1Vancassel X. et al., Numerical simulation of aerosols in an aircraft wake using a 3D LES solver and a detailed microphysical model, International Journal of Sustainable Aviation, 2014
2Rojo C. et al., Impact of alternative jet fuels on aircraft-induced aerosols, Fuel, 2014
How to cite: Donnelly, P., Bonne, N., and Vals, M.: A Modular, Object-Oriented Python Framework for Advanced SAF Microphysics Modelling, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-20263, https://doi.org/10.5194/egusphere-egu25-20263, 2025.
Aviation emissions are estimated to contribute approximately 3.5% of the global anthropogenic effective radiative forcing [3]. The goal to reduce this forcing can only be realized by a combination of measures including also new propulsion technologies. Aircraft powered by fuel cells operated with hydrogen are one promising future technology as they avoid both CO2 and NOx emissions. Additional to the reduction of these emissions generating strong contrail-cirrus has to be avoided to reduce the overall radiative forcing due to aviation emissions. Therefore it is important to investigate the contrail properties from fuel cell aircraft since they may significantly differ from current aircraft.
The number of ice crystals formed in the first few seconds of the exhaust is crucial for the radiative impact of the evolving contrail-cirrus. Among other effects the changed dynamics behind the propellers and the expected higher moisture-to-temperature ratio of the fuel cell exhaust will alter the number of formed ice crystals compared to classical jet combustion exhausts. Additional nucleation processes become important due to larger supersaturation values during the cooling of the plume. We will present the influence of these processes and different fuel cell setups on the number of formed ice crystals after the formation phase.
We simulate the formation of contrails by means of the Lagrangian Cloud Module (LCM) with detailed particle-based microphysics. To avoid computational overload we use a 0-D offline approach: suitably averaged data from a priori 3D CFD simulations of the exhaust dilution are used as input in the 0D LCM box model. This model has been used in recent studies for contrail formation simulations of a classical turbo-fan aircraft with kerosene or hydrogen combustion [1, 2]. During this work the LCM model has been adapted and extended to enable the simulation of contrail formation behind fuel cell powered aircraft. The model was applied and results are shown.
This work contributes to the collaborative effort of DLR and Airbus in assessing the climate impact of H2 contrails.
How to cite: Hillenbrand, D. and Unterstrasser, S.: Highly-resolved simulations of contrail formation generatedby fuel cell-propelled aircraft, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11289, https://doi.org/10.5194/egusphere-egu25-11289, 2025.
The largest uncertainties in current estimates of the aviation contribution to anthropogenic climate forcing are associated with aerosol-cloud interactions, particularly the role of soot, i.e., non-volatile particulate matter (nvPM), as the ice-nucleating particle (INP). Contrail processing, where ice crystals form on aircraft-emitted nvPM particles and subsequently release these particles back into the atmosphere after sublimation, influences their ice nucleation efficiency. However, to date, no aircraft emission inventory includes contrail-processed aerosol particles. In this study, we present the first comprehensive global aircraft emission inventory of contrail-processed nvPM particles, based on robust contrail simulations from the CoCiP (Contrail Cirrus Prediction) model and GAIA, a high-resolution real-life aircraft emissions inventory for the years 2019–2021. Our results show that aviation emitted a total of 2.83 × 1026 nvPM particles in 2019, with reductions of 48% and 41% in 2020 and 2021, respectively, due to COVID-19. During this period, the proportion of contrail-processed particles remained relatively consistent, with a slight reduction from 15% annually in 2019 to around 13% in 2020 and 2021. Approximately 75% of contrail-processed nvPM particles were processed by short-lived contrails. Spatially, the highest absolute concentrations of contrail-processed particles occurred over Europe and North America, while regions like the Arctic and North Atlantic exhibited the largest relative percentages due to favourable contrail formation conditions. Vertically, contrail-processed particles were primarily concentrated between 7 and 17 km, becoming increasingly dominant with altitude. Future work will focus on using this inventory in global climate models to estimate the impact of contrail processing on aviation aerosol-cloud interactions, contributing to reducing the uncertainties in aviation’s climate impact assessments.
How to cite: Qiu, K., Teoh, R., Stettler, M., Yoshioka, M., Field, P., Murray, B., and Rap, A.: A Global Aviation Emission Inventory of Contrail-Processed nvPM Particles, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11345, https://doi.org/10.5194/egusphere-egu25-11345, 2025.
Contrails are formed when the hot exhaust from the core of the engine mixes with the relatively cold ambient. Traditionally, contrail formation and its persistence is predicted using the Schmidt-Appleman (SA) criterion, which is a simple thermodynamic model developed based on the engine exhaust and ambient conditions. However, the formation of contrails is a complex multi-physics problem which lies at the intersection of thermodynamics, fluid mechanics, and physical chemistry, and is strongly dependent on engine conditions and atmospheric variables.
This being said, for modern turbofans with different engine architectures, the competing thermal and flow-field characteristics of the core jet, bypass jet, and ambient conditions play vital role in the formation of contrails in the near-field. We use RANS CFD modelling approaches to understand the macrophysical nature of contrail formation in different turbofan engines. Thermodynamic theories and analyses on the flow physics are utilized to understand the underlying mechanisms leading to contrail formation. The study finds interesting relations between the bypass ratios of the engines and potential contrail forming regions. Regions in the exhaust plume where contrails are likely to form is thus strongly dependent on the bypass ratio, or in other words, the flow-field mixing is found as an important deciding factor in contrail formation. The results are compared with the prediction from the SA criterion and the limitations and advantages of both approaches are discussed in detail. As outlook, we plan to extend this work by implementing microphysics models to complement the macrophysics results.
How to cite: Madasseri Payyappalli, M., Yin, F., and Gangoli Rao, A.: Understanding contrail formation in the near-field of modern turbofan engines, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-12684, https://doi.org/10.5194/egusphere-egu25-12684, 2025.
To reduce the considerable climate effect of aviation, the ReFuelEU aviation regulation obliges all aviation fuel suppliers to provide increasing amounts of sustainable aviation fuel (SAF) to EU airports in the coming years and decades. SAF primarily reduces aviation CO2 life-cycle emissions, but also the contrail climate effect. As SAF on average contains less aromatics, SAF-fueled aircraft emit less particulate matter, leading to lower ice crystal number concentrations with larger ice crystals in the formed contrails. In consequence, this reduces the overall contrail climate effect, as the contrails are optically thinner and less persistent. In contrast to the CO2 emissions of a flight, which are directly proportional to the fuel use, the contrail climate effect
is highly variable from flight to flight. Hence, SAF allocation to specific flights can maximise climate mitigation efforts for certain amounts of SAF, especially as long as SAF supply is limited and production capacities are still about to be scaled up.
Within the ALIGHT project, Copenhagen Airport (CPH) works towards the introduction of sustainable aviation solutions for the future. For this, one important component is knowledge on the climate-optimal SAF distribution to the flights at CPH, which we here estimate using the climate surrogate model AirClim. For the purpose, we have refined the SAF parameterisation with regard to the particulate matter reduction through SAF and use a wing span parameterisation to account for the aircraft type. The study particularly targets year 2030, as the 6% SAF mandate then is still expected to allow large climate benefits through targeted SAF use and there is still time for infrastructural adaptions. We quantify the additional climate benefit for all flights departing from CPH through targeted SAF use in those flights with the largest contrail climate effect to fuel use ratio instead of distributing it uniformly to all flights. For this, we assess the optimal SAF blending ratio, analyse various climate metrics and time horizons and cluster the flights with regard to their mean latitudes and aircraft types. The results of this study lay the ground for a complete cost-benefit analysis taking into account all aspects of infrastructure at CPH to assess practical feasibility.
How to cite: Eichinger, R., Dahlmann, K., Grewe, V., Enderle, B., Maertens, S., Kumar, S., Weder, C., Grimme, W., and Müller, L.: Simulating the climate benefit of contrail reduction through targeted SAF in 2030 at Copenhagen airport, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10666, https://doi.org/10.5194/egusphere-egu25-10666, 2025.
Currently, contrails and the induced contrail cirrus are estimated to have the strongest contribution to global warming from the aviation sector. However, the uncertainty is still large, primarily because the characteristics of contrails are strongly dependent on the atmospheric conditions at cruise altitude. Therefore, to accurately estimate the climate forcing effects of contrails, both atmospheric data and aircraft activity data must be of high quality and resolution.
The recent deployment of ADS-B transponders on aircraft has provided a new open source of aircraft activity data. The AviTeam, developed by Klenner et al. (2022), uses the ADS-B data to produce spatially and temporarily explicit emission inventories. In our work (Indo, 2024), we couple the AviTeam with the Contrail Cirrus Prediction (CoCiP) model (Schumann, 2012) to simulate the evolution of contrails from a sample of domestic flights in Norway in 2019. The results show the expected pattern of seasonal variability, with the winter (December, January and February) and autumn (September, October and November) months accounting for 81% of the annual total contrail energy forcing. Similarly, the hours between 18:00 and 06:00 were responsible for 93% of the total daily contrail energy forcings. Additionally, it is found that 2% of the flights were responsible for 80% of the annual total contrail energy forcing. Comparing our results with the literature, we also deduce that short-haul flights have significantly less contrail energy forcing per km than long-haul flights, the latter of which typically cruise in higher altitudes and are more likely to fly at night. Thus, our work reveals the specific characteristics of contrails produced by domestic flights in Norway, and also underlines the value of geospatially and temporarily explicit emissions modelling tools such as the AviTeam for modelling contrail climate forcings. Our findings also suggest that flight scheduling could be used as a tool to mitigate contrail climate forcing effects.
References
Klenner, J., Muri, H., and Strømman, A. H. (2022). High-resolution modeling ofaviation emissions in Norway. Transportation Research Part D: Transport and Environment, 109:103379. https://www.sciencedirect.com/science/article/pii/S1361920922002073.
Indo, K. (2024). Modelling of contrail climate effects with the AviTeam and the CoCiP model [master’s thesis]. https://hdl.handle.net/11250/3155585.
Schumann, U. (2012). A contrail cirrus prediction model. Geoscientific Model Development, 5(3):543–580. https://gmd.copernicus.org/articles/5/543/2012/.
How to cite: Indo, K.: Modelling of contrail climate effects with the AviTeam and the CoCiP model, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15580, https://doi.org/10.5194/egusphere-egu25-15580, 2025.
Optimizing flight trajectories to reduce the climate effect of non-CO2 aviation emissions - particularly by avoiding contrails and contrail cirrus - represents a promising strategy for mitigating aviation's environmental footprint. This approach depends on detailed knowledge of how localized aviation emissions affect the climate. Previous research has examined the influence of different meteorological conditions on aviation emissions and identified regions particularly sensitive to these effects. Tools like 4-dimensional climate change functions (CCFs) have been developed to assist sustainable air traffic management (ATM) in designing flight trajectories that minimize climate effects. However, these tools have so far been limited to specific regions, seasons, or weather scenarios [1,2].
In this study, we expand the geographic scope of the CCFs by conducting Lagrangian simulations across different extratropical regions of the northern hemisphere. Using the modular ECHAM5/MESSy atmospheric chemistry model (EMAC), we analyze contrail evolution along Lagrangian trajectories, offering insights into the temporal dynamics of contrail formation parameters and their radiative forcing effects. This approach allows for a detailed examination of the physical processes driving contrail-climate interactions, as well as their spatial and temporal variability.
A key advancement over previous CCFs studies is the application of an improved interpolation method, which transforms meteorological parameters from grid boxes onto Lagrangian trajectories with higher precision. Preliminary results indicate that this method enhances the accuracy of contrail property estimates, revealing regional differences in contrail persistence and radiative forcing that were previously unresolved. Our findings highlight the importance of refining modeling techniques to better assess contrail effects on climate at regional and global scales.
This study was funded by the European SESAR programme under Grant Agreement No. 101114785 (CONCERTO) and the German LuFo Project Dkult (Grant Agreement No. 20M2111A). High-performance supercomputing resources were provided by the German CARA Cluster in Dresden and the DKRZ Cluster in Hamburg.
References:
[1] Matthes, S., Lührs, B., Dahlmann, K., Grewe, V., Linke, F., Yin, F., Klingaman, E. and Shine, K. P.: Climate-Optimized Trajectories and Robust Mitigation Potential: Flying ATM4E, Aerospace 7(11), 156, 2020.
[2] Frömming, C., Grewe, V., Brinkop, S., Jöckel, P., Haslerud, A. S., Rosanka, S., van Manen, J., and Matthes, S.: Influence of weather situation on non-CO2 aviation climate effects: the REACT4C climate change functions, Atmos. Chem. Phys., 21, 9151–9172, https://doi.org/10.5194/acp-21-9151-2021, 2021.
How to cite: Peter, P., Matthes, S., Frömming, C., Dietmüller, S., and Grewe, V.: Estimating the Climate Effect of Contrails in Mid-Latitudes Using a Lagrangian Framework in the EMAC Model, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19067, https://doi.org/10.5194/egusphere-egu25-19067, 2025.
We present recent work in modeling the impact of the aviation industry on contrail formation and its subsequent effect on global warming by utilizing the Contrail Cirrus Prediction Model (CoCiP) with comprehensive 2019 airline data. This approach offers an in-depth, fleet-level perspective, revealing the influence on global energy forcing due to various factors including, but not limited to aircraft market class, operator region, and origin-destination pairs. Our analysis extends to a comparative study with results derived from our internally developed machine-learning (ML) emulator, the Hybrid Contrail Prediction (HyCoP) modeling framework. The HyCoP framework is designed to harness the power of physics-based CoCiP simulation data alongside satellite image-based ground truth observations to accurately predict persistent contrail formation. Central to this innovative framework is the Bayesian Deep Neural Network (BDNN) classifier. HyCoP is being developed to integrate aircraft engine-specific features, enhancing the standard inputs traditionally used in the CoCiP model. Furthermore, we detail our rigorous validation efforts for these contrail models. We employ geostationary satellite (GOES) images and data from flight campaigns such as 2023 ecoDemonstrator and 2024 Contrail Optical Depth Experiment (CODEX) to ensure the accuracy and reliability of our predictions. Our presentation includes the current status of our comprehensive start-to-end validation pipeline, which detects and tracks contrails and attributes them to their originating aircraft. This holistic approach underscores our commitment to advancing the understanding of contrail impacts on climate change through cutting-edge predictive modeling and thorough validation methodologies.
How to cite: Ray Majumder, S.: Enhanced Predictive Modeling and Validation of Persistent Contrails, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7550, https://doi.org/10.5194/egusphere-egu25-7550, 2025.
Aviation impacts Earth’s climate by the formation of contrails, where the largest fraction of the total atmospheric impact is caused by only a small fraction of flights. Forecasting of high impact regions which are likely to produce strongly warming contrails can be achieved with the Lagrangian plume model CoCiP (Contrail cirrus Prediction tool). The model calculates the instantaneous energy forcing per meter flight distance (EFm) during a contrails’ lifetime. It can be operated in two modes: Either along specific flight trajectories or on a 4D grid over an extended area. Simulations depend on meteorological input data and information on aircraft type, heading and contrail overlap. In this study we analyse the impact of these input parameters on the EFm and assess the spatial uncertainty of high-impact regions.
We use the pycontrails open-source implementation of CoCiP to simulate the potential contrail occurrence on a grid over Europe multiple times. We successively vary i) the aircraft type across an ensemble of the 10 most common types, ii) the heading from northward to eastward and iii) the meteorology across the 10-member ensemble of ECMWF ERA5 data for 2019. Additionally, we simulate the contrail formation from historical flight trajectories in 2019 provided by the Global Aviation emissions Inventory based on ADS-B (GAIA), both with and without accounting for contrail radiative interactions.
The standard deviation in EFm is largest for the aircraft ensemble, followed by the meteorology ensemble. This reveals that the aircraft type has significant impact on the climate effect from contrails. Within the aircraft ensemble, 26% of high-impact grid points are agreed upon by all ensemble members, whereas 8% are considered as high impact by only one member. The radiative interaction between contrails leads to a reduction in EFm by 2%, with a stronger effect during night than during daytime. In areas of high air traffic density, the reduction increases up to 5%.
Our results help to assess uncertainties in the prediction of contrail-sensitive airspaces and of individual flights necessary for operational contrail avoidance.
How to cite: Widmaier, K., Piontek, D., Kirschler, S., Teoh, R., Stettler, M. E. J., and Voigt, C.: Uncertainties in contrail modelling of high impact regions, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15625, https://doi.org/10.5194/egusphere-egu25-15625, 2025.
Aviation causes climate effects through both long-lived CO₂ emissions and short-lived but highly uncertain contrail cirrus. The radiative forcing (RF) of contrail cirrus is spatially and temporally very heterogeneous. This study evaluates the costs and benefits of rerouting by incorporating estimates of the social cost of CO₂ and contrail cirrus, applied to nearly half a million flights over the North Atlantic (Johansson et al., 2024). We estimate contrail cirrus formation and RF uncertainty for individual flights using CoCIP and the 10-member ERA5 ensemble from the European Centre for Medium-Range Weather Forecasts (ECMWF) (Teoh, 2022), alongside additional assumptions on forcing and efficacy uncertainty.
We explore the potential climate benefits of rerouting flights to avoid contrail formation, weighing additional fuel burnt against reduced contrail RF. Our results highlight that while rerouting can contribute to climate mitigation, its attractiveness depends on the probability that each rerouting case delivers a net climate benefit. For instance, with a 50% probability threshold (i.e., the median) that a net climate benefit is obtained, 33–35% of flights are beneficial to reroute with a 1% fuel penalty, depending on the social cost assumptions. This proportion decreases to 28–33% for a 5% fuel penalty. Raising the probability to 80% that a net climate benefit is achieved lowers the fraction of flights beneficial to reroute to 27–29% for a 1% fuel penalty and 22–27% for a 5% fuel penalty, where the ranges depend on the social cost assumptions.
In this presentation, we provide further insights from the analysis and present an analysis of the value of improved contrail forcing predictability for more effective climate impact mitigation strategies.
References
Johansson, D. J. A., Azar, C., Pettersson, S., Sterner, T., Stettler, M., & Teoh, R. (2024, May 14). The social costs of aviation: Comparing contrail cirrus and CO2. Research Square Preprints. https://doi.org/10.21203/rs.3.rs-4329434/v1
Teoh, R., Schumann, U., Gryspeerdt, E., Shapiro, M., Molloy, J., Koudis, G., Voigt, C., & Stettler, M. E. J. (2022). Aviation contrail climate effects in the North Atlantic from 2016 to 2021. Atmospheric Chemistry and Physics, 22(22), 10919–10935. https://doi.org/10.5194/acp-22-10919-2022
How to cite: Johansson, D., Azar, C., Pettersson, S., Sterner, T., Stettler, M., and Teoh, R.: Addressing Uncertainty and Rerouting Strategies in Aviation Climate Impact Assessments, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15429, https://doi.org/10.5194/egusphere-egu25-15429, 2025.
The relative humidity to ice water is crucial to determining whether or not ice crystals in contrails are able to persist. Inaccurate weather model data for this key meteorological input to contrail models is widely appreciated to be the limiting factor in current contrail models to produce accurate contrail persistence statistics. Identifying biases and constraining the inaccuracies in this weather data is needed to enable analysis of contrail models without this as a confounding factor.
Extratropical low pressure systems (storms) in the North Atlantic structure the weather in this region. These storms have a well-understood structure. Averaging composites of many storm systems is a frequently used method to observe features in both weather model output and observations. We show that a similar method can be used to identify the structures in the contrail-sustaining ice-supersaturated regions, and the regions of flight traffic through them. In-situ humidity observations give an understanding of the accuracy of the meteorological data. Humid features are seen where models are subject to saturation adjustment but can be constrained to an accurate understanding of ice-supersaturation. Conversely, downwelling air—which is typically dry—is not as well constrained when humidity does occur. This work identifies opportunities to begin exploring contrail model validation, but also acts to steer development of more accurate weather models.
How to cite: Driver, O., Stettler, M., and Gryspeerdt, E.: Flying around storms: Structured supersaturation at weather systems, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19677, https://doi.org/10.5194/egusphere-egu25-19677, 2025.
Northrop Grumman Corporation (NGC), in partnership with NASA’s Jet Propulsion Laboratory (JPL), is developing modeling capabilities for the prediction of Aircraft-Induced Cirrus (AIC) cloud generation by commercial aviation operators. This work is in support of the United States Department of Energy’s (DOE) Advanced Research Projects Agency – Energy (ARPA-E) Predictive Real-time Emissions Technologies Reducing Aircraft Induced Lines in the Sky (PRE-TRAILS) program. Leveraging NGC knowledge and flight test data on contrail prediction and formation, NGC is developing the Contrail Avoidance System (CAS) to prevent the formation of AIC by enabling aircraft to identify and avoid Ice Super Saturated Regions (ISSRs) in real time. The two key components of this work are development of a new instrument, JPL’s Y-band Temperature and Humidity Profiler (YTHP), and prediction of contrail formation and evolution to AIC using a fusion of NGC’s existing Contrail Prediction Model and the Weather Research and Forecasting (WRF) numerical weather prediction model.
YTHP is an aircraft-mounted submillimeter-wave spectroradiometer that will retrieve vertical profiles of atmospheric temperature and moisture in front of an aircraft. As part of the PRE-TRAILS program, we plan 12 flight test missions in which the YTHP sensor and our operational contrail-avoidance tools will be characterized and validated. Ground observers will track the onset and evolution of persistent contrails using photometrically calibrated cameras.
We will use WRF as a cloud-resolving regional model for the spatial domain covering the flight testing of YTHP. Our long-term modeling goals are to develop a method to insert recently created contrails into the WRF simulation to predict the evolution of contrails to persistent cirrus, and to show how assimilation of YTHP profiles improves that prediction capability. These efforts support the project goal of integrating the YTHP sensor onto aircraft, allowing flight crews to proactively respond to ISSR in the flight path minutes prior to the formation of contrails that would otherwise become AIC.
We will present results of our initial modeling work, which is aimed at assessing WRF performance for simulating ISSRs that cause persistent contrails/AIC. Our studies will include comparison of WRF ISSR representation to contrail formation flight test data previously gathered by NGC. We will also present comparisons of WRF ISSR results with areas of AIC visible in satellite images.
How to cite: Valant-Weiss, B., Deal, W., Klobas, J. E., Swanson, A., and Hauss, B.: WRF Configuration for Prediction of Aircraft-Induced Cirrus Formation, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2948, https://doi.org/10.5194/egusphere-egu25-2948, 2025.
