Quantify Convective Weather Impact to Airspace Capacity for Improved Regional Air Traffic Flow Management

The East China region has experienced over a 10% annual growth rate in traffic volume over the past decade. Convective weather is the top reason for massive flight delays in its airspace. When facing a high impact convective weather event such as a major thunderstorm system or multiple small thunderstorm cells, air traffic management (ATM) is accomplished in an ad hoc fashion based mainly on air traffic controller’s experience and workload. This methodology lacks consistency and often results in overly-conservative closing of the major routes for unnecessarily long periods of time, resulting in massive delays and slow system recovery. Through the U.S.-China Aviation Cooperation Program (ACP), experts from IMSG, NOAA/ESRL/Global Systems Division (GSD), East China Air Traffic Management Bureau (EC ATMB), and U.S. airlines are collaborating to develop an operationally-usable decision support tool (DST) to quantify convective weather impact within the current airspace configuration in East China. This DST is based on customization of GSD’s Flow Constraint Index (FCI) algorithm and applying calibrated scaling to the baseline reference clear-day maximum flow capacity. The resulting metrics, based on forecast weather and traffic information, are estimates of Waypoint Capacity, Route Segment Capacity, and Sector Capacity, which are already familiar to EC ATMB’s operational air traffic flow management (ATFM) practice. Our methodology captures the variability in impacts due to convective weather events and traffic demand, in contrast to the current static capacity estimates based on clear day and normal operations. Preliminary results using both the region’s air traffic and weather data in three consecutive summer months (June-July-August) in 2017 revealed the actual traffic patterns compared to the flight plans. These results along with other operational information specific to the region were used to tailor the FCI-based algorithm to demonstrate operationally-usable concepts in predicting airspace capacity.