Affiliations: [a] Washington State University, Pullman, WA, USA
| [b] The MITRE Corporation, McLean, VA, USA
| [c] University of North Texas, Denton, TX, USA
Correspondence:
[*]
Corresponding author: Mengran Xue, Washington State University, Pullman, WA 99164, USA. E-mail: [email protected].
Abstract: Motivated by challenges in strategic traffic flow management, a stochastic network model is introduced for the spatiotemporal evolution of weather impact at a strategic time horizon. Specifically, a model that represents weather-impact propagation using local probabilistic influences is shown to capture the rich dynamics and inherent variability in weather impact at the spatial and temporal resolution of interest. This model serves as a simulation tool to generate stochastic weather-impact trajectories for strategic air traffic management. To develop the simulator, first the underlying influence model concept is introduced. Next, an approach for parameterizing the model from probabilistic weather forecast data is developed, such that statistics of generated weather/weather-impact trajectories match the forecasts at snapshot times. An example weather-impact simulator for a particular bad-weather event, namely a long-duration convective weather event in Atlanta Center on 26 September 2010, is also developed. The framework shows promise for e.g. 1) managing weather contingencies for the airspace over a full day; 2) adjusting forecast resolution in data-limited areas for special management requirements; and 3) evaluating variability in airspace performance.
Keywords: Air traffic management, stochastic network model, network
design
