Accuracy and Risk Assessment of Rail Temperature Estimation Using Ground Observations and KMA Gridded Air Temperature
Year: 2025
Type: article
Abstract: Although wide-area monitoring of rail temperature (TR) is increasingly needed to address the heightened risk of track buckling under climate change, existing point-based analysis remain limited in spatial scalability. This study quantitatively evaluated the error characteristics of TR estimation and the associated limitations in risk assessment when using spatially gridded Air Temperature (Ta) data provided by the Korea Meteorological Administration (KMA). Measured TR from two study sites, Namsan Junction and Osong Railway Comprehensive Test Track, were used as benchmarks to compare TR estimates derived from point-based Ta and gridded Ta. A probabilistic risk assessment using cumulative distribution functions was performed with a critical TR threshold of 50 ℃, informed by actual accident cases. The analysis showed that point-based TR estimates overestimated TR by up to +9.6 ℃ during summer daytime, resulting in a calculated probability of exceeding the 50 ℃ that was 2 to 8 times higher than the actual risk. In contrast, grid-based TR estimates consistently underestimated TR, primarily due to scale-mismatch effects. This produced an opposite error pattern, with most cases indicating a 0% exceedance probability even when actual TR values surpassed the critical threshold. Based on these fundamental error characteristics, future research should focus on developing more reliable wide-area TR estimation methods by validating and fusing diverse spatial datasets, including satellite observations and high-resolution numerical models.
Language: English
Subfield: Mechanical Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: diamond
Awards: G6077269151, G6382524325
OpenAlex ID: W7117137462