Projection of Flight Cancellations and Economic Losses Caused by Future Climate Change

Hoyong Lee, Kyunghun Kim, Jong Gu Hwang-Bo, Soojun Kim

Korean Society of Hazard Mitigation · 28 October 2022

In one sentence. Applies machine learning and nearest-neighbour with genetic algorithms to downscale SSP projections, estimating flight cancellations and losses rising up to 8.29 times by 2100.

Abstract

The aviation industry plays an important role in daily life because of the increase of demand attributable to the development of air logistics as well as domestic and foreign tourism. However, the higher frequency of extreme weather caused by climate change has a large adverse effect on the operation of aircraft. As this effect is expected to increase, measures to reduce flight cancellation are needed. Therefore, in this study, the number of future flight cancellations and related economic losses were calculated for 1 3 domestic airports and six domestic airlines. To calculate the future climate of the airports, we used the recently released Shared Socioeconomic Pathways (SSP) climate change scenario. Then, we applied machine learning and the nearest neighbor with genetic algorithm method for spatial and temporal downscaling, respectively. The calculated results were applied to aircraft cancellation criteria and a damage estimation formula. Depending on the scenario, rainfall intensity increased by 2.02 to 3.54 times and wind speed increased by 1.16 to 1.24 times during 2100 to 2081. Economic losses from aircraft cancellations attributable to future climate increased by up to approximately 8.29 times. The results of this study highlight the necessity of preparing for and responding to climate change within the airline industry.

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