Periodic Reporting for period 1 - F4EClim (Flying ATM for Environment Climate)
Período documentado: 2024-09-01 hasta 2025-08-31
The overall objective of the project F4EClim is to advance the understanding and operational management of aviation’s non-CO2 climate impacts by evolving algorithmic Climate Change Functions (aCCFs) and integrating weather forecasts and climate science. The project develops extended aCCFs which can feed into a MET service on climate effects for airspace users. F4EClim explores complexity of such MET services, by identifying added value in a large-scale trajectory optimization. F4EClim concludes with recommendations and KPIs to guide stakeholders in adopting eco-efficient operations and reducing climate uncertainties.
Specifically, the objective O-1 is to extend aCCFs of CO2 and non-CO2 climate effects to cover different seasons, different regions, and identifying confidence intervals. Using advanced climate-chemistry modelling, aCCFs expand geographically, seasonally, and across diverse weather patterns while addressing uncertainties in climate science and forecasting.
The objective O-2 is to explore mitigation potentials from alternative climate-optimized trajectories together with the uncertainties in these estimates by developing advanced flight planning algorithms to identify robust, climate-optimized trajectories. The aim is to pinpoint dependable, eco-efficient paths that reduce total climate effects while quantifying performance and cost trade-offs. Trajectory optimization tools for research applications are enhanced in F4EClim and made available open-source to support benchmarking and collaborative research.
The objective O-3 is to provide stakeholders with recommendations on policy actions and measures to implement eco-efficient aircraft trajectories by improving understanding of individual trajectory climate impacts. F4EClim aims to translate scientific insights on non-CO2 effects into practical guidance for stakeholders introducing KPIs to enhance transparency of climate metrics and models.
Specifically, the objective O-1 is to extend aCCFs of CO2 and non-CO2 climate effects to cover different seasons, different regions, and identifying confidence intervals. Using advanced climate-chemistry modelling, aCCFs expand geographically, seasonally, and across diverse weather patterns while addressing uncertainties in climate science and forecasting.
The objective O-2 is to explore mitigation potentials from alternative climate-optimized trajectories together with the uncertainties in these estimates by developing advanced flight planning algorithms to identify robust, climate-optimized trajectories. The aim is to pinpoint dependable, eco-efficient paths that reduce total climate effects while quantifying performance and cost trade-offs. Trajectory optimization tools for research applications are enhanced in F4EClim and made available open-source to support benchmarking and collaborative research.
The objective O-3 is to provide stakeholders with recommendations on policy actions and measures to implement eco-efficient aircraft trajectories by improving understanding of individual trajectory climate impacts. F4EClim aims to translate scientific insights on non-CO2 effects into practical guidance for stakeholders introducing KPIs to enhance transparency of climate metrics and models.
F4EClim aimed to characterize the sources of uncertainties of non-CO2 climate effects estimates and their mathematical description, and the development of extended algorithmic Climate Change Functions (aCCFs). F4EClim project delivered a prototype of a probabilistic surrogate model describing the climate impact of NOx emissions via O3 perturbations for the extended NOx-O3 aCCFs. This version enables the estimation of the Average Temperature Response over 20 years associated with this non-CO2 effect of aviation, while providing uncertainty ranges. The modelling chain for the computation of new Climate Change Functions (CCFs) for NOx-induced O3 effects was defined. The radiative forcing caused by local NOx emissions will be simulated using a Lagrangian approach with the ECHAM/MESSy Atmospheric Chemistry Model (EMAC). This will enable the inclusion of a wider range of atmospheric situations in the development of the extended NOx-O3 aCCFs during the next phase of the project.
Furthermore, the project also aimed to enhance in-house flight planning tools (ROC, ROOST, pyTOM) and to perform large-scale trajectory optimization analyses to quantify mitigation potential and associated trade-offs. ROC has achieved major computational improvements, now enhancing efficiency by removing ensemble wind modeling and focusing on meteorological uncertainty in non-CO2 effects, particularly contrails, thereby accelerating function evaluations and improving convergence. ROOST has been extended to include free-routing capabilities within a unified framework for both structured and free airspace, enabling fair comparisons and more robust assessments of route network inefficiencies; the 2D version is complete, with the 3D version expected by the end of 2025. PyTOM, a scalable Python framework based on Dymos+OpenMDAO, enhances convergence via a discrete pre-optimization step and employs a modular cost structure supporting multiple objectives, including time, fuel, operating cost, climate impact, and convective avoidance.
In this reporting period, we focused on designing the final Hindcast analysis, which includes defining a flight scenario based on European air traffic and deriving three representative data sets of varying size and traffic volume, while ensuring broad variability in flight characteristics such as lateral extent and distance. The study for hindcast and similarity analysis identified sensitivity parameters, emphasizing changes in meteorological and operational boundary conditions, and established suitable trajectory distance metrics. The integrated Trajectory Calculation Module (iTCM) was prepared to perform reverse trajectory calculations, with the method demonstrated on exemplary trajectories. In parallel, the F4EClim aviation and climate impact service, representing the project’s final solution, is under active development, with functionalities being implemented using data from the previous project
Furthermore, the project also aimed to enhance in-house flight planning tools (ROC, ROOST, pyTOM) and to perform large-scale trajectory optimization analyses to quantify mitigation potential and associated trade-offs. ROC has achieved major computational improvements, now enhancing efficiency by removing ensemble wind modeling and focusing on meteorological uncertainty in non-CO2 effects, particularly contrails, thereby accelerating function evaluations and improving convergence. ROOST has been extended to include free-routing capabilities within a unified framework for both structured and free airspace, enabling fair comparisons and more robust assessments of route network inefficiencies; the 2D version is complete, with the 3D version expected by the end of 2025. PyTOM, a scalable Python framework based on Dymos+OpenMDAO, enhances convergence via a discrete pre-optimization step and employs a modular cost structure supporting multiple objectives, including time, fuel, operating cost, climate impact, and convective avoidance.
In this reporting period, we focused on designing the final Hindcast analysis, which includes defining a flight scenario based on European air traffic and deriving three representative data sets of varying size and traffic volume, while ensuring broad variability in flight characteristics such as lateral extent and distance. The study for hindcast and similarity analysis identified sensitivity parameters, emphasizing changes in meteorological and operational boundary conditions, and established suitable trajectory distance metrics. The integrated Trajectory Calculation Module (iTCM) was prepared to perform reverse trajectory calculations, with the method demonstrated on exemplary trajectories. In parallel, the F4EClim aviation and climate impact service, representing the project’s final solution, is under active development, with functionalities being implemented using data from the previous project
The overall goal of F4EClim is to work towards implementing eco-efficient trajectories while integrating prevailing uncertainties. First Ambition (#1) is to develop a new set of robust algorithmic climate change functions (aCCF-V2.0) describing the climate effects of CO2, NOx, H2O, and contrail cirrus over an expanded geographical and seasonal coverage. Achieving Ambition #1, will allow to enhance the Met service on climate effects in order to enable more effective climate impact mitigation through flight planning. Second Ambition (#2) is to conduct a large-scale trajectory optimization simulation experiment to explore the potentiality to mitigate climate effects with a high level of confidence at limited cost increase. This simulation experiment has been defined in the first year of the project, in order to provide an analysis exploring daily, monthly, seasonal, and yearly variations for both structured and free-routing airspace (enabling win-win analysis). Third Ambition (#3) is oriented towards the tailoring of the information to stakeholders’ needs, supporting them in the decision making towards a climate-neutral ATM system. By Ambition #4, we are also expecting to reach higher maturity at the end of the project and, eventually, incorporate the F4EClim solution as a prototype service.