Airspace throughput analysis considering stochastic weather

The estimation of the capacity of an airspace region during weather events is an important part of air traffic management. This problem must be solved ahead of time with predicted traffic demands and weather forecasts. In order to capture the uncertainty of the weather, a stochastic weather model is used. We investigate the problem of estimating the maximum capacity of an airspace region by analyzing the sector airspace geometry and a stochastic weather model. Using algorithms for computing geometric flow capacity in 2-dimensional regions, we compute the maximum capacity for an airspace having a given (deterministic) set of weather constraints. Then, we extend our results to a stochastic weather model, obtaining analytical results for weather constraints that form constraints along a line segment (e.g., placed along the flow bottleneck or along a squall line) and obtaining simulation results for a more general two-dimensional stochastic weather model. Our results allow us to determine the probability distribution of the throughput capacity of an airspace, given a probabilistic weather forecast.