Importance of Weather Conditions in a Flight Corridor

Gong Chen, Hartmut Fricke, Ostap Okhrin and Judith Rosenow
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Gong Chen: Chair of Econometrics and Statistics esp. Transportation, Dresden University of Technology, 01187 Dresden, Germany
Hartmut Fricke: Chair of Air Transport Technology and Logistics, Institute of Logistics and Aviation, Dresden University of Technology, 01062 Dresden, Germany
Judith Rosenow: Chair of Air Transport Technology and Logistics, Institute of Logistics and Aviation, Dresden University of Technology, 01062 Dresden, Germany

Stats, 2022, vol. 5, issue 1, 1-27

Abstract: Current research initiatives, such as the Single European Sky Air Traffic Management Research Program, call for an air traffic system with improved safety and efficiency records and environmental compatibility. The resulting multi-criteria system optimization and individual flight trajectories require, in particular, reliable three-dimensional meteorological information. The Global (Weather) Forecast System only provides data at a resolution of around 100 km. We postulate a reliable interpolation at high resolution to compute these trajectories accurately and in due time to comply with operational requirements. We investigate different interpolation methods for aerodynamic crucial weather variables such as temperature, wind speed, and wind direction. These methods, including Ordinary Kriging, the radial basis function method, neural networks, and decision trees, are compared concerning cross-validation interpolation errors. We show that using the interpolated data in a flight performance model emphasizes the effect of weather data accuracy on trajectory optimization. Considering a trajectory from Prague to Tunis, a Monte Carlo simulation is applied to examine the effect of errors on input (GFS data) and output (i.e., Ordinary Kriging) on the optimized trajectory.

Keywords: spatial interpolation; Kriging; neural network; gradient boosting machines; Monte Carlo simulation (search for similar items in EconPapers)
JEL-codes: C1 C10 C11 C14 C15 C16 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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