Future Airport Performance Under Weather Conditions: Combining Historical Statistics with Emerging New Technologies and Procedures

Abstract

The ability to predict and optimize airport capacity is crucial for efficient air traffic management. We introduce a novel approach to evaluate and forecast the long-term weather-dependent usability of new technologies and procedures aiming to increase runway capacity at airports. By leveraging historical weather data from METAR reports covering extended time periods (20+ years) and linking specific weather conditions to separation requirements between arrivals and departures, our methodology assesses the long-term impact of weather on airport operations. We employ a standardized discrete event simulation to recreate demand patterns and traffic processes over these long timescales, yielding comprehensive performance indicators in the form of weather-induced levels of service for runway operations allowing the evaluation of weather-dependent usability over time. The benefits of this approach are demonstrated through an exemplary application to the Super Close Runway Operations (SupeRO) concept, highlighting potential improvements in airport capacity utilization. By harnessing historical weather data and simulation-based analysis, our method enables airports to better anticipate and adapt new technologies and procedures to future weather conditions, ultimately enhancing overall air traffic management efficiency and safety.