Assessment of the Impacts of Thunderstorm on Flight Operations at Murtala Mohammed International Airport, Ikeja, Lagos State, Nigeria

Abstract

The inefficiency of the aviation industry and the persistent rise in aviation hazards have been linked to weather phenomena. As a result, researchers are looking for better solutions to the problem. The study examined the impact of thunderstorms on flight operations at Murtala Mohammed International Airport, Lagos. The data on thunderstorms and flight operations were sourced from Nigerian Meteorological Agency (NiMet) and Nigerian Airspace Management Agency (NAMA) respectively. In order to meet the research target, descriptive statistics (mean, standard deviation, and charts) and inferential statistics (Pearson’s Product Moment Correlation (PPMC) and Regression) were used. The significance level for all inferential analyses was set at 5% (0.05). The study revealed that 77.4% of thunderstorms occurred during the rainy season (April-October) while 22.6% occurred during the dry season (November-March). It also revealed some fluctuating movements of a thunderstorm in the study area. According to the findings, thunderstorms occur most frequently at the airport in June and less frequently in January and December. The study also discovered that thunderstorms at the airport are positively and significantly related to flight delays and cancellations, while the association between flight diversions and thunderstorm occurrence is positive but statistically insignificant. Furthermore, flight delays, flight diversions, and flight cancellations interact positively among themselves. The regression result of the study revealed that a 1% increase in thunderstorm occurrence leads to a 19.4% increase in flight delay, a 7.1% increase in flight cancellation, and a 4.3% increase in flight diversion. As a result, the study presented various regression models that may be utilized to make predictions. The study proposes consistent thunderstorm observation at the airport and steady forecasts using the regression models, based on the findings. However, it further recommends that pilots, air traffic controllers, and meteorologists be trained and retrained so that they can provide better and more efficient services.