Representative Weather-Impact Scenarios for Strategic Traffic Flow Planning

This paper proposes a methodology for using ensemble weather forecasts to assist in air traffic flow contingency management. Specifically, the weather ensemble members are converted into scenarios of weather impact, and performance metrics are formulated to assess the similarity of these scenarios. Metrics for measuring weather impacts on both en route sectors and airports are considered in scenario clustering. Representative scenarios are selected using a proposed index, which quantifies the representativity of scenarios and addresses the requirements of representative selections. In a quantitative experiment, historical demand and weather forecast data from a sample weather day are simulated to demonstrate the proposed methodology. When combining en route and terminal impact metrics, a weighting approach between two metric categories is employed to reflect operational preferences since their tradeoff may influence the clustering results as well as the representative selection. Lastly, the strategic flow management plans for a few selected representative scenarios are developed and their performance results are analyzed. It shows that the scenarios in the same cluster have a similar response to the plan that is the most effective on its representative scenario.