Airline schedule recovery in collaborative flow management and weather forecast uncertainty

This paper presents a modeling approach to evaluate flow management concepts that enable rerouting automation capabilities coordinated across multi-air route traffic control centers (ARTCC). The focus of our analysis is on the problem of convective weather forecast uncertainty in conditions where actual convective weather has limited both airport and airspace sector capacity. A convective weather forecast model is used to replicate weather forecasts that are stochastic in nature, and is embedded in a dynamic simulation environment representing the US National Airspace System (NAS) operations. The flow concepts evaluated focus on extending today's flow management services which currently use automated decision aids primarily centered on the problem of airport arrival capacity and increasingly require manual intervention to coordinate aircraft routes around crowded airspace and severe weather areas. The paper presents results of the Boeing National Flow Model (NFM) simulation for two flow management control strategies with current and enhanced convective weather forecasting performance.