Highlights A new formulation to measure the resilience performance of airports under severe weather events was developed. A big data based on actual air performance was adopted for the empirical analysis. Modal substitution to HSR service is found to be an important tactic of airport resilience.

    Abstract The increased severe weather events in recent years as a result of global climate change has created a substantial challenge for aviation system operation. Although transportation engineers and planners have attempted to improve system resilience through the adaptation of new technologies and the implementation of various strategies to achieve effective risk management, it remains unclear how resilience performance (measured by the speed of recovery) of airports varies in different severe weather events and what factors may explain such variations. This paper addresses these fundamental questions using the aviation system in China as an example. A resilience metric, which reflects the speed of recovery (bounce back) from a shock, was developed to measure the performance of airport resilience under various severe weather conditions. In addition, an empirical econometric analysis was conducted based on a dataset that includes both detailed aviation performance and weather conditions for the period of October 2016 – September 2017. The research findings show that airport resilience to severe weather events does vary substantially based on factors, such as weather conditions, airport capacity, and the level of modal substitution. In particular, the recovery time of air services in central and south China tends to be relatively longer in thunderstorms than other weather conditions. The study also confirms that modal substitution is a very effective resilience tactic of the transportation system as the recovery speed of air service was found to be faster by 22.9% if an alternative mode, such as high-speed rail (HSR) service was also available in the city.


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    Title :

    Measuring the performance of airport resilience to severe weather events


    Contributors:
    Zhou, Lei (author) / Chen, Zhenhua (author)


    Publication date :

    2020-01-01




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




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