Leveraging Weather and Climate Data for Greener Flight Trajectories
F4EClim
Sustainable flight trajectory planning for climate-compatible aviation
The F4EClim project (Flying ATM for Environment Climate) is developing advanced methods to reduce the climate impact of air traffic. Using weather forecasts and climate research, CO₂ emissions, contrails, and other non-CO₂ emissions are to be considered during flight planning. The goal is to optimise flight trajectories so that they are both ecologically and economically efficient, contributing to climate-compatible aviation. (Symbolic image)
Credit:
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Project duration: September 2024 to February 2027
Innovative Climate-Analytical Methods in Flight Planning
F4EClim (Flying ATM for Environment Climate) aims to make aviation more climate-efficient. The focus is on the further development of so-called algorithmic Climate Change Functions (aCCFs). These functions integrate precise weather data and current climate research to minimise uncertainties in the calculation of the climate impacts of CO₂, contrails, ozone, methane, and H2O. The research is based on findings from the predecessor projects ATM4E and FlyATM4E.
Research and Development Focus
As part of the project, the aCCFs will be further developed. Their geographical application range will be expanded beyond the North Atlantic, considering various seasonal and meteorological conditions. Another key project element is the development of a web-based climate service for aviation, which will make the research results available in real time. This service is intended to support the aviation community in selecting climate-compatible flight trajectories.
In addition, optimisation algorithms for flight planning will be developed, enabling the identification of flight trajectories that are both climate-efficient and cost-effective. These algorithms consider not only CO₂ emissions but also other non-CO₂ climate emissions, such as contrails and ozone. In this context, the DLR Institute of Air Transport is working on further developing the trajectory optimiser TOM into "pyTOM" to improve these processes further.
Hindcasting and Model Validation
To verify and fine-tune the models, so-called "hindcasting" methods will be used. Flight trajectories optimised for weather forecasts will be analysed using real-weather data to improve the accuracy of predictions and refine model specifications.
The DLR Institute of Air Transport will conduct a comprehensive hindcasting study aimed at assessing the robustness and uncertainties of climate-optimised flight planning. This study will also derive specific recommendations for stakeholders in the air traffic system.
The F4EClim project – Leveraging Weather and Climate Data for Greener Flight Trajectories
Partners and DLR institutes involved: Delft University of Technology (TU Delft), Universidad Carlos III de Madrid (UC3M); DLR Institute of Air Transport
Results and Recommendations
Through the project work, flight trajectories and their climate impacts should be better understood, targeted improvements should be made possible, incorrect re-routings should be avoided, and regulatory decision-makers should be better informed.
At the end of the project, a set of recommendations for the aviation industry will be created, including key performance indicators (KPIs) to help stakeholders advance the implementation of eco-efficient flight trajectories. The goal is to raise awareness of the non-CO₂ effects of air traffic and support the long-term implementation of climate-optimised flight planning.
