Spatial Interpolation of BDS/GNSS Precipitable Water Vapor Using LimiX in the Beijing–Tianjin–Hebei Region

Ground-based BeiDou Navigation Satellite System/Global Navigation Satellite System (BDS/GNSS) observations can be used to retrieve precipitable water vapor (PWV) at high temporal resolution, but the estimates are confined to discrete station locations. We applied the pretrained tabular regression model LimiX, using its 2M variant, to PWV interpolation over the Beijing–Tianjin–Hebei region in 2024. Station spatial features paired with PWV estimates served as context without regional retraining. Comparisons with inverse distance weighting, ordinary kriging, universal kriging, and geographically weighted regression used PWV derived from the ERA5 reanalysis and a separate fixed-station holdout experiment. Against ERA5, LimiX had an annual mean absolute difference of 1.1 mm and a root mean square difference of 1.5 mm. Its spatial correlation coefficient (SCC) was 0.97. LimiX had the lowest root mean square difference relative to ERA5 in all seasons and months. Interpolation validation against observations at 13 withheld GNSS stations gave an annual root mean square error of 1.3 mm, close to both kriging methods. During a heavy precipitation event on 9–10 August 2024, mean PWV began increasing before quantitative precipitation estimation (QPE) rose markedly and remained elevated after the QPE peak. High-PWV and high-QPE areas overlapped locally at some epochs. LimiX combined close ERA5 agreement with station-level interpolation errors comparable to kriging, providing regional PWV fields without retraining for the study area.