Establishment and assessment of a zenith wet delay (ZWD) augmentation model

The zenith wet delay (ZWD) accuracy is one of the most important factors affecting the convergence time and the positioning precision in precise point positioning processing. Taking into account the limitation of the empirical and blind ZWD models, the correlations between the ZWD and temperature and water vapor pressure at each point of the global 1º × 1º grid were analyzed. Based on the global grid of augmentation coefficients derived from the European Centre for Medium-Range Weather Forecasts (ECMWF) data with a temporal resolution of 6 h from 2011 to 2014, a new ZWD augmentation model was established, which is a weighting of differences between the in situ meteorological quantities and those from the GPT3 model. The performance of the proposed model was assessed against three traditional models using different data sources in 2015, i.e., the ECMWF grids and globally distributed International GNSS Service (IGS) sites. The numerical results show that the proposed model outperforms the other three models with the largest RMSE/RRMSE improvement, reaching 1.08 cm/11.37% and 0.99 cm/9.8% when comparing the ECMWF grids and IGS sites, respectively.