This randomized control trial provides evidence for the efficacy of airline-led contrail avoidance to reduce aviation's climate impact. By integrating ML forecasts into standard flight planning, dispatchers routed flights to avoid warming contrails. Satellite validation showed an 11.6 % overall reduction in contrails, increasing to 62 % for flights strictly following the optimized paths, all with no significant fuel penalty.

It can be difficult to know if a given aircraft made a contrail. Existing methods that can be applied to any aircraft either use numerical weather data or satellite observations. In this work we create a new method by combining weather data and observations together. By comparison to in-situ measurements we show that the new method is superior to previous methods.

Operational strategies such as eco-efficient flight routing have potential to reduce aviation’s climate effect. A collaborative workflow integrating aviation weather forecasting, flight planning, air traffic control, and climate benefit assessment was developed and tested in D-KULT. Innovative developments demonstrate substantial progress on how to identify alternative trajectories but also highlight remaining challenges, including uncertainties in weather forecast and non-CO₂ climate effects.

Targeted contrail avoidance consists of rerouting aircraft to minimise the formation of warming contrails. However, current predictions of contrail climate impact are highly uncertain. In this study, we show that some reroutings that were predicted to be beneficial for the climate are in fact damaging it. We further demonstrate that the risk of unintentionally damaging the climate can and should be included in the decision-making of contrail avoidance.