Periodic Reporting for period 4 - TBO-MET (Meteorological Uncertainty Management for Trajectory Based Operations)
Période du rapport: 2017-12-01 au 2018-05-31
The context of the TBO-Met project can be described as follows. Uncertainty is a key factor that affects the achievement of the high-level goal set for the Single European Sky of increasing the capacity of the Air Traffic Management (ATM) system while maintaining high safety standards and improving the overall performance, and in particular the weather uncertainty, which is one of the main sources of uncertainty that affect ATM. Therefore, to achieve that goal, the uncertainty levels in ATM have to be reduced and new strategies to deal with the remaining uncertainty must be found.
In this project the problem of analysing and quantifying the effects of meteorological uncertainties in Trajectory Based Operations (TBO) has been addressed, focussing on two particular problems: 1) trajectory planning under meteorological uncertainties and 2) sector demand forecast under meteorological uncertainties, which correspond to two different scales: trajectory scale and sector scale. More especifically, three research topics have been addressed: 1) trajectory planning at pre-tactical level (mid-term planning) under meteorological uncertainties, 2) storm avoidance at tactical level (short-term planning and execution), and
3) sector demand analysis under meteorological uncertainties, both at pre-tactical and tactical levels. The weather information is obtained from Ensemble Prediction Systems (EPS) and Nowcasts, which provide two types of meteorological uncertainties: wind uncertainty and convective zones (including individual storm cells).
At the trajectory scale, the main objective has been to improve the predictability of aircraft trajectories when subject to weather uncertainty keeping acceptable levels of efficiency, both at the mid-term level (up to three hours before departure) and at the short-term level (during the flight). At the sector scale, the main objective has been to increase the accuracy of the prediction of sector demand when weather uncertainty is taken into account. To help in achieving these objectives, a survey among the stakeholders involved has been performed. The main result of the survey has been a first-hand expert description of current practice and future expectations, which has served as a valuable reference for the project activities.
The results obtained show that the specific objectives of TBO-Met have been fully achieved, namely:
1. The trade-off between predictability and efficiency can be quantified, considering wind uncertainty and convective risk at pre-tactical level, and the uncertain evolution of thunderstorms at tactical level.
2. The sector demand uncertainty can be measured, both, at pre-tactical and tactical levels, considering as sources of uncertainty wind and storm-cell location, respectively.
The importance of this project for society is linked to the benefits for the passengers and the different stakeholders expected from the outcome of the project.
In this project the problem of analysing and quantifying the effects of meteorological uncertainties in Trajectory Based Operations (TBO) has been addressed, focussing on two particular problems: 1) trajectory planning under meteorological uncertainties and 2) sector demand forecast under meteorological uncertainties, which correspond to two different scales: trajectory scale and sector scale. More especifically, three research topics have been addressed: 1) trajectory planning at pre-tactical level (mid-term planning) under meteorological uncertainties, 2) storm avoidance at tactical level (short-term planning and execution), and
3) sector demand analysis under meteorological uncertainties, both at pre-tactical and tactical levels. The weather information is obtained from Ensemble Prediction Systems (EPS) and Nowcasts, which provide two types of meteorological uncertainties: wind uncertainty and convective zones (including individual storm cells).
At the trajectory scale, the main objective has been to improve the predictability of aircraft trajectories when subject to weather uncertainty keeping acceptable levels of efficiency, both at the mid-term level (up to three hours before departure) and at the short-term level (during the flight). At the sector scale, the main objective has been to increase the accuracy of the prediction of sector demand when weather uncertainty is taken into account. To help in achieving these objectives, a survey among the stakeholders involved has been performed. The main result of the survey has been a first-hand expert description of current practice and future expectations, which has served as a valuable reference for the project activities.
The results obtained show that the specific objectives of TBO-Met have been fully achieved, namely:
1. The trade-off between predictability and efficiency can be quantified, considering wind uncertainty and convective risk at pre-tactical level, and the uncertain evolution of thunderstorms at tactical level.
2. The sector demand uncertainty can be measured, both, at pre-tactical and tactical levels, considering as sources of uncertainty wind and storm-cell location, respectively.
The importance of this project for society is linked to the benefits for the passengers and the different stakeholders expected from the outcome of the project.
For the trajectory planning problem at pre-tactical level (up to three hours before departure), a methodology has been developed to plan efficient trajectories with low levels of uncertainty. In particular, two problems have been analysed: On one hand, the trade-off between predictability (measured by the flight-time dispersion) and cost-efficiency (flight time or fuel consumption) considering only uncertain winds, and, on the other, the trade-off between exposure to convective risk and cost-efficiency considering now uncertain winds and convection risk.
At tactical level (during the flight), a probabilistic trajectory predictor under thunderstorm activity has been developed, taking into account the uncertainty in the location of the convective cells. The output is an ensemble of deviation trajectories that avoid the possible storm realisations and reattach to the optimal reference route (computed at the pre-tactical phase). An already existing deterministic tool for generating the deviation trajectories (DIVMET) has been adapted to account for the uncertainty in the cell evolution.
For the sector demand problem, the objective has been to quantify the impact of trajectory planning under weather uncertainty (as performed at the pre-tactical level, with enhanced predictability) on sector demand. A methodology has been developed to analyse the uncertainty of sector demand (probabilistic sector loading) in terms of the uncertainty of the individual trajectories. The approach is based on the statistical characterization of the entry and occupancy counts, and is quite general, not depending on the specific tools developed in the project.
The methodologies developed have been validated using an already existing advanced simulation infrastructured (NAVSIM), in conjuction with a storm avoidance tool (DIVMET). All concepts developed have been fully validated, except one which has shown that, from a sector demand point of view, the dispersion of the individual trajectories may not be properly characterized just by the flight time dispersion, and that different ways of that characterization should be explored.
The results have shown that, when weather forecast uncertainty is taken into account,
• the predictability of aircraft trajectories can be increased,
• the storm avoidance strategy can be better anticipated, and
• the accuracy of sector demand forecast can be improved;
hence, the overall conclusion is that the ATM efficiency can be enhanced by integrating into the ATM planning process the available information about the uncertainty of weather forecasts.
At tactical level (during the flight), a probabilistic trajectory predictor under thunderstorm activity has been developed, taking into account the uncertainty in the location of the convective cells. The output is an ensemble of deviation trajectories that avoid the possible storm realisations and reattach to the optimal reference route (computed at the pre-tactical phase). An already existing deterministic tool for generating the deviation trajectories (DIVMET) has been adapted to account for the uncertainty in the cell evolution.
For the sector demand problem, the objective has been to quantify the impact of trajectory planning under weather uncertainty (as performed at the pre-tactical level, with enhanced predictability) on sector demand. A methodology has been developed to analyse the uncertainty of sector demand (probabilistic sector loading) in terms of the uncertainty of the individual trajectories. The approach is based on the statistical characterization of the entry and occupancy counts, and is quite general, not depending on the specific tools developed in the project.
The methodologies developed have been validated using an already existing advanced simulation infrastructured (NAVSIM), in conjuction with a storm avoidance tool (DIVMET). All concepts developed have been fully validated, except one which has shown that, from a sector demand point of view, the dispersion of the individual trajectories may not be properly characterized just by the flight time dispersion, and that different ways of that characterization should be explored.
The results have shown that, when weather forecast uncertainty is taken into account,
• the predictability of aircraft trajectories can be increased,
• the storm avoidance strategy can be better anticipated, and
• the accuracy of sector demand forecast can be improved;
hence, the overall conclusion is that the ATM efficiency can be enhanced by integrating into the ATM planning process the available information about the uncertainty of weather forecasts.
The progress of the project amounts to the methodologies developed to quantify and better understand the impact of wind uncertainty and convective weather in trajectory planning and sector demand, both at mid-term and short-term levels. The overall outcome has been the development of three methodologies, as follows:
• for the mid-term trajectory planning problem, the concept developed is a stochastic optimisation methodology capable of trading-off cost-efficiency and predictability and/or exposure to convective risk;
• for the storm avoidance problem, the concept developed is a probabilistic trajectory predictor with storm avoidance, taking into account the uncertainty in the location of the convective cells; and
• for the sector demand problem, the concept developed is an ensemble-based stochastic methodology to predict the sector demand based on the uncertainty of the individual trajectories.
In relation to these three topics, the specific achievements of the project can be summarised as follows:
• the capability of generating more predictable trajectories considering the uncertainty of weather predictions;
• the capability of being better informed about the evolution of the hazardous convective weather regions;
• the capability of improving the accuracy of the sector demand forecast.
The expected impacts, from the point of view of the overall efficiency of the ATM system, are the following:
• for passengers, reductions of delays
• from the airlines perspective, improvement of flight predictability, reduction of risks, and better-informed decision making;
• from the side of Air Navigation Service Providers, better allocation of resources and reduction of Air Traffic Control workload; and
• from the Network Manager side, better identification of the Air Traffic Flow and Capacity Management measures to be applied (for example, rerouting, advancing traffic, or slot allocation).
• for the mid-term trajectory planning problem, the concept developed is a stochastic optimisation methodology capable of trading-off cost-efficiency and predictability and/or exposure to convective risk;
• for the storm avoidance problem, the concept developed is a probabilistic trajectory predictor with storm avoidance, taking into account the uncertainty in the location of the convective cells; and
• for the sector demand problem, the concept developed is an ensemble-based stochastic methodology to predict the sector demand based on the uncertainty of the individual trajectories.
In relation to these three topics, the specific achievements of the project can be summarised as follows:
• the capability of generating more predictable trajectories considering the uncertainty of weather predictions;
• the capability of being better informed about the evolution of the hazardous convective weather regions;
• the capability of improving the accuracy of the sector demand forecast.
The expected impacts, from the point of view of the overall efficiency of the ATM system, are the following:
• for passengers, reductions of delays
• from the airlines perspective, improvement of flight predictability, reduction of risks, and better-informed decision making;
• from the side of Air Navigation Service Providers, better allocation of resources and reduction of Air Traffic Control workload; and
• from the Network Manager side, better identification of the Air Traffic Flow and Capacity Management measures to be applied (for example, rerouting, advancing traffic, or slot allocation).