LVNL uses a Decision Support Tool (DST) to manage and mitigate delays up to four hours ahead. Accurate weather forecasts play a crucial role in accurately predicting the airport’s capacity. Specifically low visibility conditions due to fog severely limit the capacity due to the large separation between aircraft that is needed to ensure safe operations. Fog can arise and dissipate within a matter of minutes. Besides that, it can occur on very small spatial scales, as small as a couple hundred metres. Ordinary weather forecasting tools are often incapable of capturing this very small-scale and short-lived nature of fog. Using machine learning algorithms to forecast fog poses a promising solution to this issue. Using observations on the airfield, visibility forecasts can be made for multiple areas at the airport. A small-scale, accurate fog forecast greatly increases the capability of air traffic controllers to anticipate lower capacities, and therefore timely mitigate delays.
Graduated: November 2024