GNSS water vapor tomography based on Kalman filter with optimized noise covariance

Comparing Discrete and Empirical Troposphere Delay Models: A Global IGS‐Based Evaluation

“…Note that the GPT3 model does not provide ZHD and ZWD values directly but provides various meteorological parameters, the formula of which is as follows (Lagler et al., 2013): $$$\begin{array}{c}r(t)={A}_{0}+{A}_{1}\,\cos \left(\frac{doy}{365.25}2\pi \right)+{B}_{1}\,\sin \left(\frac{doy}{365.25}2\pi \right)+{A}_{2}\,\cos \left(\frac{doy}{365.25}4\pi \right)+{B}_{2}\,\sin \left(\frac{doy}{365.25}4\pi \right)\end{array}$$$ where r ( t ) represents the meteorological parameters to be estimated; doy denotes the day of the year; A 0 represents its average value; and A 1 , B 1 and A 2 , B 2 are their annual and semiannual amplitudes, respectively. Then the relevant meteorological parameters were substituted into the Saastamoinen model to obtain the required ZHD (Shi, Xu, et al., 2023; Yang, Gong, et al., 2023). The corresponding formula is shown as follows: $$$\begin{array}{c}\text{ZHD}=2.2768\times P/(1-0.00266\,\cos \,2\,\varphi -0.00028h)\end{array}$$$ where φ and h denote the latitude and ellipsoidal height of the site, respectively (Yang, Sun, et al., 2023).…”