• this study proposes a novel ZHD model (NZHD) that requires input of surface atmospheric pressure and water vapor pressure. • To address the challenge of obtaining real-time meteorological observations, we constructed a high-resolution grid model of atmospheric pressure and water vapor pressure for the Chinese region based on real-time meteorological observations. • Compared to traditional models such as SAAS and HGPT2, the NZHD model demonstrates improved accuracy, particularly in low-latitude regions. • Finally, we evaluated the performance of the NZHD model in PWV retrieval using radiosonde data as the reference. • The results indicate that PWV extracted using the NZHD model not only exhibits higher precision but also resolves the issue of negative PWV values, thereby enhancing the reliability of PWV data. Accurate estimation of the Zenith Hydrostatic Delay (ZHD) is crucial for Global Navigation Satellite System (GNSS) positioning and the retrieval of Precipitable Water Vapor (PWV). Building upon the Saastamoinen ZHD model (SAAS), this study proposes a novel ZHD model (NZHD) that requires input of surface atmospheric pressure and water vapor pressure. To address the challenge of obtaining real-time meteorological data, we constructed a high-resolution grid model of atmospheric pressure and water vapor pressure for the Chinese region based on real-time ground-based GNSS meteorological observations. Compared to traditional models such as SAAS and HGPT2, the NZHD model demonstrates improved accuracy, particularly in low-latitude regions. Finally, we evaluated the performance of the NZHD model in PWV retrieval using radiosonde data as the reference. The results indicate that PWV extracted using the NZHD model not only exhibits higher precision but also resolves the issue of negative PWV values, thereby enhancing the reliability of PWV data.
Zhang et al. (Sun,) studied this question.