The Decoupling Effect Analysis of Meteorological Comfort on Urban Rail Transit Ridership

Abstract This study investigates the decoupling relationship between meteorological comfort and urban rail transit ridership in China. Daily meteorological data and passenger volume data from 28 major cities were processed to construct a meteorological comfort index using the entropy weighting method, in which precipitation levels were converted into continuous values based on national standards. A decoupling model was then applied to examine the dynamic interaction between weather comfort and transit use. The analysis identifies three classes of decoupling states: Class A, where passenger travel remains stable despite unfavorable weather; Class B, where moderate sensitivity to meteorological variation is observed; and Class C, where travel is strongly influenced by weather conditions. Results show that most cities predominantly fall under Class B, but with notable fluctuations across seasons and regions. The findings highlight that meteorological comfort does not uniformly determine ridership, but instead reveals differentiated patterns of resilience and vulnerability across urban rail systems. This contributes to a deeper understanding of how external environmental factors interact with public transit demand and provides methodological guidance for improving the robustness of transport planning under climate variability.