Evaluation of an Airport Capacity Prediction Model for Strategizing Air Traffic Management

Strategic air traffic flow management addresses predictions of significant capacity/demand imbalances four or more hours in the future. The current planning process for mitigating the imbalances that result from large-scale weather events relies heavily on decision makers mentally translating weather forecasts into traffic impact. To support quantitative weather-impact assessment in the planning process, we have proposed methods that estimates capacity loss of airspace and airports from weather forecast. In this study, we will improve and validate a model for airport capacity estimation that takes into account the forecast of ceiling, visibility, and wind direction and also local preferences on runway configuration. We will compare the differences among the observed weather and the forecast scenarios from multiple weather products, such as Terminal Area Forecast and Short Range Ensemble Forecast. The metrics for prediction performance comparison will be proposed, and the differences in performance among forecast products and among airports will be examined and concluded. It is expected that although the decision makers do not have the knowledge of the actual weather at the time of planning for airport capacity, lessons regarding the progression of predictions made along with multiple forecast updates can enlighten prediction uncertainty and future decision making. The insights and results provided in this study will also inform whether the current forecast products has sufficient resolution and accuracy to aid strategic air traffic flow management.