A Method for Building the Grid-Based Atmospheric Weighted Mean Temperature Model Considering the Hourly NSTLR

The weighted mean temperature (Tm) is a critical parameter for converting zenith wet delay (ZWD) to precipitable water vapor (PWV) in Global Navigation Satellite System (GNSS) meteorology. Unlike conventional approaches, this study develops a novel high-precision atmospheric Tm grid model with enhanced spatiotemporal resolution through the incorporation of hourly near-surface temperature lapse rates (NSTLR). The core methodology encompasses two principal components: regional estimation of hourly NSTLR variations and establishment of a corresponding Tm grid model. Validation was conducted using ERA5 reanalysis datasets and in situ measurements from 109 meteorological stations across Shandong Province and Sichuan Province, China. Compared with no environmental lapse rate (ELR) correction and constant ELR correction, the accuracy of the constructed Tm grid model improved by 31.59% and 11.51%, respectively. Notably, in high-altitude areas, the improvements were even more substantial, reaching 58.65% and 21.28%, respectively. Therefore, the Tm model constructed in this study has significant practical significance for building ground-based meteorological observation systems, especially for regions with significant terrain variations.