With the availability to high-accuracy a priori zenith wet delay (ZWD) data, the positioning efficiency of the precise point positioning (PPP) processing can be effectively improved, including accelerating the convergence time and improving the positioning precision, in ground-based Global Navigation Satellite System (GNSS) technology. Considering the limitations existing in the state-of-the-art ZWD models, this paper established and evaluated a new in-situ meteorological observation-based grid model for estimating ZWD named GridZWD using the radiosonde data and the European Centre for Medium-Range Weather Forecasts (ECWMF) data. The results show that ZWD has a strong correlation with the meteorological parameter water vapor pressure in continental and high-latitude regions. The root of mean square error (RMS) of 24.6 mm and 36.0 mm are achievable by the GridZWD model when evaluated with the ECWMF data and the radiosonde data, respectively. An accuracy improvement of approximately 10%~30% compared with the state-of-the-art models (e.g., the Saastamoinen, Hopfield and GPT2w models) can be found for the new built model.