Articles | Volume 16, issue 13
https://doi.org/10.5194/gmd-16-3723-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-16-3723-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
06 Jul 2023
Model description paper |
| 06 Jul 2023
| 06 Jul 2023
Robust 4D climate-optimal flight planning in structured airspace using parallelized simulation on GPUs: ROOST V1.0
Abolfazl Simorgh
CORRESPONDING AUTHOR
Department of Aerospace Engineering, Universidad Carlos III de Madrid, Madrid, Spain
Manuel Soler
Department of Aerospace Engineering, Universidad Carlos III de Madrid, Madrid, Spain
Daniel González-Arribas
Department of Aerospace Engineering, Universidad Carlos III de Madrid, Madrid, Spain
Florian Linke
Hamburg University of Technology (TUHH), Hamburg, Germany
Deutsches Zentrum für Luft- und Raumfahrt, Air Transportation Systems, Hamburg, Germany
Benjamin Lührs
Hamburg University of Technology (TUHH), Hamburg, Germany
Maximilian M. Meuser
Hamburg University of Technology (TUHH), Hamburg, Germany
Deutsches Zentrum für Luft- und Raumfahrt, Air Transportation Systems, Hamburg, Germany
Simone Dietmüller
Deutsches Zentrum für Luft- und Raumfahrt, Institut für Physik der Atmosphäre, Oberpfaffenhofen, Germany
Sigrun Matthes
Deutsches Zentrum für Luft- und Raumfahrt, Institut für Physik der Atmosphäre, Oberpfaffenhofen, Germany
Hiroshi Yamashita
Deutsches Zentrum für Luft- und Raumfahrt, Institut für Physik der Atmosphäre, Oberpfaffenhofen, Germany
Feijia Yin
Faculty of Aerospace Engineering, Delft University of Technology, Delft, the Netherlands
Federica Castino
Faculty of Aerospace Engineering, Delft University of Technology, Delft, the Netherlands
Volker Grewe
Deutsches Zentrum für Luft- und Raumfahrt, Institut für Physik der Atmosphäre, Oberpfaffenhofen, Germany
Faculty of Aerospace Engineering, Delft University of Technology, Delft, the Netherlands
Sabine Baumann
Deutsches Zentrum für Luft- und Raumfahrt, Institut für Physik der Atmosphäre, Oberpfaffenhofen, Germany
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Cited
17 citations as recorded by crossref.
- The applicability of Zermelo's equation to indirect and direct optimization of commercial aircraft flights A. Jafarimoghaddam & M. Soler
- Network-level aircraft trajectory planning via multi-agent deep reinforcement learning: Balancing climate considerations and operational manageability F. Baneshi et al.
- Integrating Non-CO2 climate impact considerations in air traffic management: Opportunities and challenges F. Baneshi et al.
- Feasibility of integrating multiple climate impact estimation models to enhance confidence in environmentally-friendly aircraft trajectory optimization A. Simorgh & M. Soler
- Integrating realistic 3D aircraft trajectory optimization with climate impact metrics for sustainable aviation R. Chevallier et al.
- Concept of robust climate-friendly flight planning under multiple climate impact estimates A. Simorgh et al.
- Decision-making strategies implemented in SolFinder 1.0 to identify eco-efficient aircraft trajectories: application study in AirTraf 3.0 F. Castino et al.
- The ozone radiative forcing of nitrogen oxide emissions from aviation can be estimated using a probabilistic approach P. Rao et al.
- Pathways for including non-carbon dioxide aviation climate effects in the European Emission Trading System V. Grewe et al.
- Contrail minimization through altitude diversions: A feasibility study leveraging global data E. Roosenbrand et al.
- Climate Impact of Optimizing ATM and ATC Procedures for Mitigating CO2 and Non-CO2 Emissions D. Bianco et al.
- The climate opportunities and risks of contrail avoidance J. Smith et al.
- Comparison of Actual and Time-Optimized Flight Trajectories in the Context of the In-Service Aircraft for a Global Observing System (IAGOS) Programme O. Boucher et al.
- Climate-aware 4D trajectory optimization for polar flights considering weather uncertainties Q. Zhang
- A deep multi-agent reinforcement learning framework for climate-aware aircraft trajectory planning considering air traffic complexity F. Baneshi et al.
- Climate-optimized flight planning can effectively reduce the environmental footprint of aviation in Europe at low operational costs A. Simorgh & M. Soler
- Robust 4D climate-optimal aircraft trajectory planning under weather-induced uncertainties: Free-routing airspace A. Simorgh et al.
17 citations as recorded by crossref.
- The applicability of Zermelo's equation to indirect and direct optimization of commercial aircraft flights A. Jafarimoghaddam & M. Soler
- Network-level aircraft trajectory planning via multi-agent deep reinforcement learning: Balancing climate considerations and operational manageability F. Baneshi et al.
- Integrating Non-CO2 climate impact considerations in air traffic management: Opportunities and challenges F. Baneshi et al.
- Feasibility of integrating multiple climate impact estimation models to enhance confidence in environmentally-friendly aircraft trajectory optimization A. Simorgh & M. Soler
- Integrating realistic 3D aircraft trajectory optimization with climate impact metrics for sustainable aviation R. Chevallier et al.
- Concept of robust climate-friendly flight planning under multiple climate impact estimates A. Simorgh et al.
- Decision-making strategies implemented in SolFinder 1.0 to identify eco-efficient aircraft trajectories: application study in AirTraf 3.0 F. Castino et al.
- The ozone radiative forcing of nitrogen oxide emissions from aviation can be estimated using a probabilistic approach P. Rao et al.
- Pathways for including non-carbon dioxide aviation climate effects in the European Emission Trading System V. Grewe et al.
- Contrail minimization through altitude diversions: A feasibility study leveraging global data E. Roosenbrand et al.
- Climate Impact of Optimizing ATM and ATC Procedures for Mitigating CO2 and Non-CO2 Emissions D. Bianco et al.
- The climate opportunities and risks of contrail avoidance J. Smith et al.
- Comparison of Actual and Time-Optimized Flight Trajectories in the Context of the In-Service Aircraft for a Global Observing System (IAGOS) Programme O. Boucher et al.
- Climate-aware 4D trajectory optimization for polar flights considering weather uncertainties Q. Zhang
- A deep multi-agent reinforcement learning framework for climate-aware aircraft trajectory planning considering air traffic complexity F. Baneshi et al.
- Climate-optimized flight planning can effectively reduce the environmental footprint of aviation in Europe at low operational costs A. Simorgh & M. Soler
- Robust 4D climate-optimal aircraft trajectory planning under weather-induced uncertainties: Free-routing airspace A. Simorgh et al.
Saved (final revised paper)
Latest update: 04 May 2026
Short summary
This paper addresses the robust climate optimal trajectory planning problem under uncertain meteorological conditions within the structured airspace. Based on the optimization methodology, a Python library has been developed, which can be accessed using the following DOI: https://doi.org/10.5281/zenodo.7121862. The developed tool is capable of providing robust trajectories taking into account all probable realizations of meteorological conditions provided by an EPS computationally very fast.
This paper addresses the robust climate optimal trajectory planning problem under uncertain...
