A Calibrated GPT3 (CGPT3) Model for the Site-Specific Zenith Hydrostatic Delay Estimation in the Chinese Mainland and Its Surrounding Areas

Abstract

The prior zenith hydrostatic delay (ZHD) is an essential parameter for the Global Navigation Satellite System (GNSS) and very long baseline interferometry (VLBI) high-precision data processing. Meanwhile, the precise ZHD facilitates the separation of the high-precision zenith wet delay (ZWD) to derive precipitable water vapor (PWV). This paper analyzes the temporal variations in the residuals between GPT3 ZHD and reference ZHD from radiosonde (RS) sites, and a calibrated GPT3 (CGPT3) model is proposed for the site-specific ZHD estimation in the Chinese mainland and its surrounding areas based on the annual, semi-annual, and diurnal variations in residuals. Based on the validation using modeling RS data, the mean absolute error (MAE) and root mean square (RMS) of the CGPT3 model are 7.3 and 9.6 mm, respectively. The validation with RS ZHD not involved in the modeling suggests that the MAE and RMS of the CGPT3 model are 7.9 and 10.2 mm, respectively. These results show improvements of 16.8%/16.8% and 14.3%/13.6%, respectively, compared with the MAE and RMS of the GPT3 model and the newly proposed model (GTrop). In addition, the CGPT3 model has excellent spatial and temporal stability in the study area.

Keywords

• the GPT3 model
• zenith hydrostatic delay (ZHD)
• error analysis
• calibration
• precipitable water vapor (PWV) retrieval