Comparison of actual and time-optimized flight trajectories in the context of the In-service Aircraft for a Global Observing System (IAGOS) programme

Boucher, O., Bellouin, N. ORCID: https://orcid.org/0000-0003-2109-9559, Clark, H., Gryspeerdt, E. and Karadayi, J. (2023) Comparison of actual and time-optimized flight trajectories in the context of the In-service Aircraft for a Global Observing System (IAGOS) programme. Aerospace, 10 (9). 744. ISSN 2226-4310 doi: 10.3390/aerospace10090744

Abstract/Summary

Airlines optimize flight trajectories in order to minimize their operational costs, of which fuel consumption is a large contributor. It is known that flight trajectories are not fuel-optimal because of airspace congestion and restrictions, safety regulations, bad weather and other operational constraints. However the extent to which trajectories are not fuel-optimal (and therefore CO2-optimal) is not well known. In this study we present two methods for optimizing the flight cruising time by taking best advantage of the wind pattern at a given flight level and for constant airspeed. We test these methods against actual flight trajectories recorded under the In-service Aircraft for a Global Observing System (IAGOS) programme. One method is more robust than the other (computationally faster) method, but when successful, the two methods agree very well with each other, with optima generally within of the order of 0.1%. The IAGOS actual cruising trajectories are on average 1% longer than the computed optimal for the transatlantic route, which leaves little room for improvement given that by construction the actual trajectory cannot be better than our optimum. The average degree of non-optimality is larger for some other routes and can be up to 10%. On some routes there are also outlier flights that are not well optimized; however the reason for this is not known.

Item Type	Article
URI	https://reading-clone.eprints-hosting.org/id/eprint/113011
Identification Number/DOI	10.3390/aerospace10090744
Refereed	Yes
Divisions	Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
Publisher	MDPI
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