Temporal and spatial Bayesian network modelling for improved fog forecasting. This project aims to improve the accuracy of fog forecasting by explicitly modelling the spatial and temporal uncertainties surrounding fog formation. It is expected weather forecast services will adopt our approach to improve their predictions of fog, which will in turn help transport companies save costs, cut emissions and improve safety.
New real-time risk indicators to improve the efficiency, environmental impact and safety of air traffic management. Air-traffic demand is constantly rising, and Australia is responsible for the management of 11 per cent of the world's airspace. This project aims to develop risk indicators which will enable us to monitor air-safety risks on a constantly updated basis.