Multi-model ensemble wake vortex prediction

TL;DR: In this paper, a Multi-Model Ensemble (MME) approach called Reliability Ensemble Averaging (REA) is adapted and used to the wake vortex predictions.

Abstract: Purpose Wake vortices that are generated by an aircraft as a consequence of lift constitute a potential danger to the following aircraft. To predict and avoid dangerous situations, wake vortex transport and decay models have been developed. Being based on different model physics, they can complement each other with their individual strengths. This paper investigates the skill of a Multi-Model Ensemble (MME) approach to improve prediction performance. Therefore, this paper aims to use wake vortex models developed by NASA (APA3.2, APA3.4, TDP2.1) and by DLR (P2P). Furthermore, this paper analyzes the possibility to use the ensemble spread to compute uncertainty envelopes. Design/methodology/approach An MME approach called Reliability Ensemble Averaging (REA) is adapted and used to the wake vortex predictions. To train the ensemble, a set of wake vortex measurements accomplished at the airports of Frankfurt (WakeFRA), Munich (WakeMUC) and at a special airport Oberpfaffenhofen was applied. Findings The REA approach can outperform the best member of the ensemble, on average, regarding the root-mean-square error. Moreover, the ensemble delivers reasonable uncertainty envelopes. Practical implications Reliable wake vortex predictions may be applicable for both tactical optimization of aircraft separation at airports and airborne wake vortex prediction and avoidance. Originality/value Ensemble approaches are widely used in weather forecasting, but they have never been applied to wake vortex predictions. Until today, the uncertainty envelopes for wake vortex forecasts have been computed among others from perturbed initial conditions or perturbed physics as well as from uncertainties from environmental conditions or from safety margins but not from the spread of structurally independent model forecasts.