An Approach to En-Route Sector Demand Prediction subject to Thunderstorms

Abstract

In this paper, a probabilistic approach to en-route sector demand prediction at tactical level subject to thunderstorm activity is presented. The source of uncertainty is the location of the convective cells affecting the sector. An ensemble-based stochastic methodology is developed that takes into account the stochastic evolution of the detected convective cells. The sector demand is predicted for short forecasting horizons (less than one hour); the analysis is based on the statistical characterization of the occupancy count. A realistic application is presented. The results show that the sector demand can be accurately predicted at tactical level when thunderstorm uncertainties are considered. The effects of the stochastic evolution of the convective cells on the demand prediction are quantified.