# A Method to Improve the Distribution of Observations in GNSS Water Vapor Tomography
## 3 Experiment and Analysis  
### Experiment Description and GNSS Data Processing Strategy  
As shown in Figure 2, Hong Kong was selected as the tomography area, the scope of which was 113.87\({}^{\circ}\)-114.35\({}^{\circ}\) for longitude, 22.19\({}^{\circ}\)-22.54\({}^{\circ}\) for latitude and 0-8.0 km for altitude. The vertical resolution was 800 m and the horizontal resolution was 0.06\({}^{\circ}\) in longitude, and 0.05\({}^{\circ}\) in latitude. A tomography grid containing 8 \(\times\) 7 \(\times\) 10 voxels was obtained. To determine which boundary point to use when improving the distribution of observations, the tomography area was divided into four regions (northwest, southwest, southeast, and northeast). Twelve GNSS stations of the Hong Kong Satellite Positioning Reference Station Network (SatRet), which were evenly distributed in the four regions, were selected in the tomography modeling. Another GNSS station and radiosonde station (45004) were used to check the result of the water vapor tomography. The information of each site was shown in Table 1. A, B, C, and D in the table represent boundary points and their geodetic coordinates were (22.54\({}^{\circ}\), 113.87\({}^{\circ}\), 8.0 km), (22.19\({}^{\circ}\), 113.87\({}^{\circ}\), 8.0 km), (22.19\({}^{\circ}\), 114.35\({}^{\circ}\), 8.0 km), and (22.54\({}^{\circ}\), 114.35\({}^{\circ}\), 8.0 km). To validate the proposed method, GNSS observation data of DOY 182 to 188, 2017 were selected with a sampling rate of 30 s. The data from a radiosonde station at 00:00 and 12:00 UTC was collected when the sounding balloon was launched daily. In this paper, two schemes, including the conventional method, which was considered as Scheme #1, and the proposed method which was regarded as Scheme #2, are determined. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Station Name**} & \multirow{2}{*}{**Latitude**} & \multirow{2}{*}{**Longitude**} & \multirow{2}{*}{**Height**} & \multirow{2}{*}{**Location**} & \multicolumn{2}{c}{**Boundary Points of**} \\  & & & & & **Virtual SWV** \\ \hline HKKT & 22.4449 & 114.0666 & 34.5764 & & \\ HKLT & 22.4181 & 113.9966 & 125.922 & Northwest & B, C, D \\ HKSL & 22.3720 & 113.9279 & 95.2972 & & \\ \hline HKPC & 22.2849 & 114.0378 & 18.1303 & & \\  & HKMW & 22.2558 & 114.0032 & 194.9461 & Southwest & A, C, D \\
**tomographic** & HKNP & 22.2491 & 113.8939 & 350.6723 & & \\ \hline HKSC & 22.3222 & 114.1412 & 20.2386 & & \\  & HKOH & 22.2477 & 114.2286 & 166.4011 & Southeast & A, B, D \\  & HKLM & 22.2190 & 114.1201 & 8.5536 & & \\ \hline HKWS & 22.4343 & 114.3354 & 63.7909 & & \\  & T430 & 22.4947 & 114.1382 & 41.3228 & Northeast & A, B, C \\  & HKST & 22.3953 & 114.1842 & 258.7045 & & \\ \hline \multirow{2}{*}{**Station for test**} & HKSS & 22.4311 & 114.2693 & 38.7135 & Northeast & \\  & 45004 & 22.31 & 114.17 & 66.0 & Southeast & \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Information of stations and boundary points. Figure 2: Geographic distribution of GNSS, radiosonde station (**left**) and 3-D tomographic voxels (**right**). The GAMIT 10.61 software was adopted for the GNSS troposphere estimation based on the double-differenced model. Tropospheric parameters among the network were strongly correlated because of the presence of a short baseline between GNSS receivers in the tomographic area. Few International GNSS Service (IGS) stations (BJFS, LHAZ, and SHAO) were incorporated into the solution model to reduce this correlation [32; 33; 34]. The GAMIT processing strategy for tropospheric estimation is summarized in Table 2. LC_AUTCLN indicates that the observable was the ionosphere-free linear combination, and BASELINE shows that orbital or EOP parameters were not estimated. The unknown parameters, including ZTD at 2-h intervals and troposphere delay gradients at 4-h intervals, are estimated using the least square method. By interpolation, ZTD and troposphere delay gradients with 30 s sampling rate are obtained. To achieve the wet delay gradients, [PERSON] et al.