Estimation of High Temporal and Spatial Resolution GNSS ZWD in Rainfall Regions and Analysis of Its Coupling Mechanism With Rainfall Events

The application of global navigation satellite system (GNSS) meteorology has gained prominence in recent years, and the GNSS-derived zenith wet delay (ZWD) has become a focus of research due to its intrinsic connection to atmospheric water vapor dynamics. However, the inherent spatiotemporal variability of ZWD poses significant challenges in achieving precise estimations, thereby constraining its data utility. To address this limitation, we propose a deep geographically weighted regression network (DeepGWR-Net) model designed for high spatiotemporal-resolution (0.1°, 1 h) ZWD estimation. This model calculates ZWD using geographic coordinates (longitude, latitude, and elevation), temperature, and pressure parameters. The model demonstrated excellent performance, with mean absolute error (MAE) and root mean square error (RMSE) values of 6.46 and 8.30 mm, respectively, representing improvements of 41.2% and 23.9%, and 39.5% and 24.3% over the multiple linear regression (MLR) method and convolutional neural network (CNN) model, respectively. Leveraging the fifth generation ECMWF reanalysis for the global land climate and weather (ERA5)-Land reanalysis data (0.1°, 1 h), we generated high-resolution ZWD grids by incorporating 3-D positional information, temperature, and pressure data. A comprehensive spatiotemporal coupling analysis was conducted using a persistent precipitation event over mainland France and adjacent regions from October 18 to November 18, 2023, employing correlation analysis, lag analysis, and geographically weighted regression (GWR) techniques. Key findings reveal predominantly positive ZWDprecipitation correlations across most regions, with localized areas influenced by the Mediterranean climate, showing a mixture of positive and negative correlations. It is worth noting that ZWD exhibits a characteristic 312 h window of dynamic changes before precipitation events. Furthermore, the response of ZWD to short-duration intense rainfall is significantly more pronounced across diverse rainfall types, and extreme rainfall events show a synchronized surge effect between ZWD and precipitation intensity. Collectively, these results substantiate significant regional spatiotemporal co-variation and spatial coupling mechanisms between ZWD and precipitation patterns.