Imagine if pilots had a weather map that showed not just storms, but where their planes would create heat-trapping clouds. This tool uses satellite data and AI to predict these 'contrails' before they happen. By avoiding these specific air pockets, planes can fly in a way that doesn't warm the planet.
Aviation's non-CO2 impact on global warming is highly uncertain due to weather and regional variations. There is currently no accurate way for airlines to predict and avoid the specific airspace conditions that create warming contrails.
The project is building AI models for radiative forcing prediction and a 'E-CONTRAIL Dashboard Visualization Tool' (D4.2).
If you are a commercial airline dealing with high carbon offset costs and climate regulations — this project developed AI models that predict radiative forcing of contrails. This allows for flight path adjustments to reduce non-CO2 warming impacts.
If you are an ANSP dealing with inefficient airspace routing — this project developed a visualization dashboard tool. This helps you guide aircraft away from volumes of airspace that cause large global warming impacts.
If you are a consultancy dealing with uncertain aviation climate data for corporate clients — this project developed remote sensing algorithms for contrail detection. This provides a more accurate way to quantify the radiative forcing of ice clouds.
Based on available project data, no commercial pricing or licensing costs are mentioned; the project is funded by an EU contribution of EUR 997,500.
The project uses data-archive numerical weather forecasts and historical traffic to train AI models, suggesting a design intended for broad aviation airspace application.
Based on available project data, specific IP or licensing terms are not provided, though the project is coordinated by Universidad Carlos III de Madrid.
The project is building a visualization tool in a dashboard to provide early and accurate predictions of high-impact airspace volumes for aviation users.
The project period runs from 2023-06-01 to 2025-11-30, with several technical objectives currently in progress.
The consortium is purely academic and research-driven, consisting of 4 partners from 3 countries (BE, ES, SE). With 2 universities and 2 research organizations and 0% industry participation, the project is focused on scientific validation and AI development rather than immediate commercial productization.
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