Caroline Forster

Assessment of a Convective Weather Nowcasting and Tracking Algorithm Based on Delay Reduction Potential at Munich Airport (Part I)

This work presents the first part of an economic assessment of Rad-TRAM, which detects, tracks and predicts up to one hour heavy precipitation cells by using weather radar data. Rad-TRAM has been developed at DLR and will be assessed by analyzing delay data at Munich Airport during convective weather events. Delay reduction potential underlying operational adaptation through advanced weather information serves as assessment metric to quantify the economic benefit of the algorithm. Advanced weather information refers to the tracking, nowcasting and visualization of severe areas within thunderstorms. Delay data is evaluated during convective impact within the boundaries of terminal airspace of Munich airport and coverage areas within this airspace are considered regarding delay behavior. Arrival traffic is affected by mean individual delay rates of up to 21 minutes whereas departure traffic is more evenly impacted during convective impact. A delay analysis of time periods before and after convective impact reveals that there is potential for delay reduction, if advanced weather information is provided in these periods as well as in the period of convective activity.