This content is not included in your SAE MOBILUS subscription, or you are not logged in.
Modeling Weather Impact on Ground Delay Programs
ISSN: 1946-3855, e-ISSN: 1946-3901
Published October 18, 2011 by SAE International in United States
Citation: Wang, Y. and Kulkarni, D., "Modeling Weather Impact on Ground Delay Programs," SAE Int. J. Aerosp. 4(2):1207-1215, 2011, https://doi.org/10.4271/2011-01-2680.
Scheduled arriving aircraft demand may exceed airport arrival capacity when there is abnormal weather at an airport. In such situations, Federal Aviation Administration (FAA) institutes ground-delay programs (GDP) to delay flights before they depart from their originating airports. Efficient GDP planning depends on the accuracy of prediction of airport capacity and demand in the presence of uncertainties in weather forecast. This paper presents a study of the impact of dynamic airport surface weather on GDPs. Using the National Traffic Management Log, effect of weather conditions on the characteristics of GDP events at selected busy airports is investigated. Two machine learning methods are used to generate models that map the airport operational conditions and weather information to issued GDP parameters and results of validation tests are described.