A weather related causal analysis on consolidated delay at Newark Liberty International Airport

The closure of the European airspace due to the eruption of the Icelandic volcano Eyjafjallajokull in 2010 proved a major challenge for airlines and aviation authorities on a global scale. In contrast, more seasonal adverse meteorological conditions afflict many airports in the northern eastern seaboard of the United States. Newark Liberty International Airport (KEWR) is a representative airport that endures severe weather based delays. This dissertation explores the utilisation of Bayesian Networks (BN) and heuristic analyses to investigate weather based delays at Newark Liberty International airport (KEWR). In particular, it aims to understand which weather variables (namely, precipitation, visibility and wind) have the most impact on weather based delays at KEWR in contrast to past studies that have studied more generic weather phenomena (e.g. thunderstorms) at the same airport. An analysis using temporal functionality with Bayesian Networks (BN) software and heuristic analyses was conducted. Data extracted from weather and aviation based websites was extracted using software. The quality of the information was cross referenced with official data sources and validated using BN tools. The results revealed a causal correlation chain between crosswinds above a certain threshold and high delays at KEWR at various points in the experimentation. Though other meteorological elements examined had an impact on delays, airport authorities and airlines can mitigate these factors to a certain scale using Federal Aviation Authority (FAA) approved technology and training. Consequently, the implications could be significant on existing FAA and regional policy with Ground Delay Program (GDP) and Noise Abatement Procedures (NAP). These policies can be profound and far reaching for airlines, in terms of operating procedures and fuel cost implications. These findings can further alter the balance between efficiency, public safety and airline costing affecting all major stakeholders as this dissertation will investigate.

Grantor dc:publisher.institution

Department of Computer Science

Year dc:date.issued

2013

Author dc:creator

• O'Loghlen, Gerald Philip

Advisor dc:contributor.advisor

• Mbogho, Audrey J W

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/11427/6639

OAI identifier oai:identifier

oai:open.uct.ac.za:11427/6639