Abstract

Compared to the zenith hydrostatic delay (ZHD) obtained from the Saastamonien model based on in-situ measured meteorological (IMM) data and radiosonde-derived weighted mean temperature (Tm), the ZHD and Tm deviations of the GPT3 model have shown obvious periodic trends. This article analyzed the seasonal variations of GPT3-ZHD and GPT3-Tm during the 2016–2020 period in the Yangtze River Delta region, and the new improved ZHD and Tm models were established by the multi-order Fourier function. The precision of the improved-ZHD model was verified using IMM-ZHD products from 7 GNSS stations during the 2016–2020 period. Furthermore, the precisions of improved Tm and precipitable water vapor (PWV) were verified by radiosonde-derived Tm and PWV in the 2016–2019 period. Compared with the IMM-ZHD and GNSS-PWV products, the mean Bias and RMS of GPT3-ZHD are −0.5 mm and 2.1 mm, while those of GPT3-PWV are 2.7 mm and 11.1 mm. Compared to the radiosonde-derived Tm, the mean Bias and RMS of GPT3-Tm are −0.8 K and 3.2 K. The mean Bias and RMS of the improved-ZHD model from 2019 to 2020 are −0.1 mm and 0.5 mm, respectively, decreasing by 0.4 mm and 1.6 mm compared to the GPT3-ZHD, while those of the improved-Tm are −0.6 K and 2.7 K, respectively, decreasing by 0.2 K and 0.5 K compared to GPT3-Tm. The mean Bias and RMS of PWV calculated by GNSS-ZTD, improved-ZHD, and improved-Tm are 0.5 mm and 0.6 mm, respectively, compared to the GNSS-PWV, decreasing by 2.2 mm and 10.5 mm compared to the GPT3-PWV. It indicates that the improved ZHD and Tm models can be used to obtain the high-precision PWV. It can be applied effectively in the retrieval of high-precision PWV in real-time in the Yangtze River Delta region.

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