The current best-estimate of the global annual mean radiative forcing (RF) attributable to contrail cirrus is thought to be 3 times larger than the RF from aviation's cumulative CO₂ emissions. Here, we simulate the global contrail RF for 2019–2021 using reanalysis weather data and improved engine emission estimates along actual flight trajectories derived from Automatic Dependent Surveillance–Broadcast telemetry. Our 2019 global annual mean contrail net RF (62.1 mW m⁻²) is 44 % lower than current best estimates for 2018 (111 [33, 189] mW m⁻², 95 % confidence interval). Regionally, the contrail net RF is largest over Europe (876 mW m⁻²) and the USA (414 mW m⁻²), while the RF values over East Asia (64 mW m⁻²) and China (62 mW m⁻²) are close to the global average, because fewer flights in these regions form persistent contrails resulting from lower cruise altitudes and limited ice supersaturated regions in the subtropics due to the Hadley Circulation. Globally, COVID-19 reduced the flight distance flown and contrail net RF in 2020 (−43 % and −56 %, respectively, relative to 2019) and 2021 (−31 % and −49 %, respectively) with significant regional variations. Around 14 % of all flights in 2019 formed a contrail with a net warming effect, yet only 2 % of all flights caused 80 % of the annual contrail energy forcing. The spatiotemporal patterns of the most strongly warming and cooling contrail segments can be attributed to flight scheduling, engine particle number emissions, tropopause height, and background radiation fields. Our contrail RF estimates are most sensitive to corrections applied to the global humidity fields, followed by assumptions on the engine particle number emissions, and are least sensitive to radiative heating effects on the contrail plume and contrail–contrail overlapping. Using this sensitivity analysis, we estimate that the 2019 global contrail net RF could range between 34.8 and 74.8 mW m⁻².

Climate impact models of the non-${\mathrm{CO}}_2$ emissions of aviation are still subject to significant uncertainties. Condensation trails, or contrails, are one of these non-${\mathrm{CO}}_2$ effects. In order to validate the contrail simulation models, a dataset of observations covering the entire lifetime of the contrails will be required, as well as the characteristics of the aircraft which produced them. This study carries on the work on contrail observation from geostationary satellite by proposing a new way to track contrails and identify the flight that produced it using geostationary satellite infrared images, weather data as well as air traffic data. It solves the tracking and the identification problem as one, each process leveraging information from the other to achieve a better overall result. This study is a new step towards a consistent contrail dataset that could be used to validate contrail models.

Aircraft condensation trails, also known as contrails, contribute a substantial portion of aviation’s overall climate footprint. Contrail impacts can be reduced through smart flight planning that avoids contrail-forming regions of the atmosphere. While previous studies have explored the operational impacts of contrail avoidance in simulated environments, this paper aims to characterize the feasibility and cost of contrail avoidance precisely within a commercial flight planning system. This study leverages the commercial Flightkeys 5D algorithm, developed by Flightkeys GmbH, with a prototypical contrail forecast model based on the Contrail Cirrus Prediction (CoCiP) model to simulate contrail avoidance on 49 411 flights during the first two weeks of June 2023, and 35 429 flights during the first two weeks of January 2024. The utilization of a commercial flight planning system enables high-accuracy estimates of additional cost and fuel investments by operators to achieve estimated reductions in contrail-energy forcing and overall flight global warming potential. The results show that navigational contrail avoidance will require minimal additional cost (0.08%) and fuel (0.11%) investments to achieve notable reductions in contrail climate forcing (−73.0%). This simulation provides evidence that contrail mitigation entails very low operational risks, even regarding fuel. This study aims to serve as an incentive for operators and air traffic controllers to initiate contrail mitigation testing as soon as possible and begin reducing aviation’s non- CO 2 emissions.

Objective: The recent emphasis on outcomes-based medical research has motivated a need for technology that allows researchers and clinicians to reach a larger and more diverse subject population for recruitment and testing. Design: This article reports on open-source mobile software (TabSINT) that enables researchers to administer customised hearing tests and questionnaires on tablets located across multiple sites. Researchers create and modify test protocols using text-based templates and deploy it to the tablets via a cloud-based repository or USB-computer connection. Results are exported locally to the tablet SD card and can also be automatically posted to a cloud-based database. Results: Between 2014 and 2019, TabSINT collected 25,000+ test results using more than 200+ unique test protocols for researchers located worldwide. Conclusions: TabSINT is a powerful software system with the potential to greatly enhance research across multiple disciplines by enabling access to subject cohorts in remote and disparate locations. Released open-source, this software is available to researchers across the world to use and adapt to their specific needs. Researchers with engineering resources can contribute to the repository to extend the capability and robustness of this software.

The global annual mean contrail climate forcing may exceed that of aviation's cumulative CO₂ emissions. As only 2 %–3 % of all flights are likely responsible for 80 % of the global annual contrail energy forcing (EF_contrail), re-routing these flights could reduce the occurrence of strongly warming contrails. Here, we develop a contrail forecasting tool that produces global maps of persistent contrail formation and their EF_contrail formatted to align with standard weather and turbulence forecasts for integration into existing flight planning and air traffic management workflows. This is achieved by extending the existing trajectory-based contrail cirrus prediction model (CoCiP), which simulates contrails formed along flight paths, to a grid-based approach that initializes an infinitesimal contrail segment at each point in a 4D spatiotemporal grid and tracks them until their end of life. Outputs are provided for N aircraft-engine groups, with groupings based on similarities in aircraft mass and engine particle number emissions: N=7 results in a 3 % mean error between the trajectory- and grid-based CoCiP, while N=3 facilitates operational simplicity but increases the mean error to 13 %. We use the grid-based CoCiP to simulate contrails globally using 2019 meteorology and compare its forecast patterns with those from previous studies. Two approaches are proposed to apply these forecasts for contrail mitigation: (i) monetizing EF_contrail and including it as an additional cost parameter within a flight trajectory optimizer or (ii) constructing polygons to avoid airspace volumes with strongly warming contrails. We also demonstrate a probabilistic formulation of the grid-based CoCiP by running it with ensemble meteorology and excluding grid cells with significant uncertainties in the simulated EF_contrail. This study establishes a working standard for incorporating contrail mitigation into flight management protocols and demonstrates how forecasting uncertainty can be incorporated to minimize unintended consequences associated with increased CO₂ emissions from re-routes.

Observations of contrails are vital for improving our understanding of the contrail formation and life cycle, informing models, and assessing mitigation strategies. Here, we developed a methodology that utilises ground-based cameras for tracking and analysing young contrails (< 35 min) formed under clear-sky conditions, comparing these observations against reanalysis meteorology and simulations from the contrail cirrus prediction model (CoCiP) with actual flight trajectories. Our observations consist of 14 h of video footage recorded over 5 different days in Central London, capturing 1582 flight waypoints from 281 flights. The simulation correctly predicted contrail formation and absence for around 75 % of these waypoints, with incorrect contrail predictions occurring at warmer temperatures than those with true-positive predictions (7.8 K vs. 12.8 K below the Schmidt–Appleman criterion threshold temperature). When evaluating contrails with observed lifetimes of at least 2 min, the simulation's correct prediction rate for contrail formation increases to over 85 %. Among all waypoints with contrail observations, 78 % of short-lived contrails (observed lifetimes < 2 min) formed under ice-subsaturated conditions, whereas 75 % of persistent contrails (observed lifetimes > 10 min) formed under ice-supersaturated conditions. On average, the simulated contrail geometric width was around 100 m smaller than the observed (visible) width over its observed lifetime, with the mean underestimation reaching up to 280 m within the first 5 min. Discrepancies between the observed and simulated contrail formation, lifetime, and width can be associated with uncertainties in reanalysis meteorology due to known model limitations and sub-grid-scale variabilities, contrail model simplifications, uncertainties in aircraft performance estimates, and observational challenges, among other possible factors. Overall, this study demonstrates the potential of ground-based cameras to create essential observational and benchmark datasets for validating and improving existing weather and contrail models.