P6. Integrating weather prediction models into ATM planning (‘IWA’)

2 – Data-driven trajectory prediction

3 – Efficient provision and use of meteorological information in ATM

Weather has a strong impact on ATM. Inefficient weather avoidance procedures and inaccurate prognosis lead to longer aircraft routes and, as a result, to fuel waste and increased negative environmental impact. A better integration of weather information into the operational ATM-system will ultimately improve the overall air traffic safety and efficiency.

Covid-19 pandemics affected aviation severely, resulting in an unprecedented reduction of air traffic, and gave the opportunity to study the flight performance in non-congested scenarios. We discovered noticeable inefficiencies and environmental performance degradation, which persisted despite significant reduction of traffic intensity. The PhD thesis proposes a methodology that allows us to distinguish which factors have the highest impact on which aspects of arrival performance in horizontal and vertical dimensions.

Academic Excellence in ATM and UTM Research (AEAR) group operating within the Communications and Transport Systems (KTS) division at Linköping University (LIU), together with the Research and Development at Luftfartsverket (LFV, Swedish ANSP) develops optimization techniques to support efficient decision-making for aviation authorities.

In this thesis, we apply probabilistic weather modelling techniques, taking into account the influence of bad weather conditions on the solutions developed in our related projects and integrate them into the corresponding optimization frameworks. First, the PhD student enhanced the optimization framework for arrival route planning in TMA, with the convective weather avoidance technique. Next, the probabilistic weather products were used to obtain an ensemble of staffing solutions, from which the probability distributions of the number of necessary ATCOs were derived. The modelling is based on the techniques recently developed within several SESAR projects addressing weather uncertainty challenges. The proposed solutions were successfully tested using the historical flight data from Stockholm Arlanda airport and five airports in Sweden planned for remote operation in the future.