## 3 Evaluation and Application of PWV Derived from CPRAP
### Performance of CPRAP-Derived PWV
#### 3.1.3 Accuracy Analysis of Satellite-Derived PWV Product  
To validate the performance of L2 PWV product provided by the FY-3A/MERSI, the corresponding PWV product over the period of 2012 to 2013 in China was selected and compared with that from the GNSS and RS, respectively. The PWV data of FY-3A/MERSI at GNSS and RS stations were first obtained by averaging the gridded PWV data with the range of 20 pixel nearby the GNSS/RS station [52]. In terms of time matching, the data for FY-3A/MERSI are changed to match the mean of the hour to the GNSS hour data. Figure 7 gives the RMS and Bias distributions of PWV difference between FY-3A/MERSI and GNSS/RS in China over the period of 2012 to 2013. It can be observed that the overall accuracy of FY-3A/MERSI is relatively low in China, especially in the south of China with a large PWV value. Furthermore, the Bias between FY-3A/MERSI and GNSS shows a positive correlation in the north of China and a negative correlation in south of China, whereas that between FY-3A/MERSI and RS has no evident correlation. Table 4 gives the statistical result of averaged RMS, Bias and MAE at those GNSS and RS stations, respectively over the period of 2012 to 2013. It can be found that the averaged RMS, Bias and MAE between FY-3A/MERSI and GNSS/RS are 4.46/4.61 mm, 0.56/ -0.33 mm and 3.61/3.79 mm, respectively. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Value** & **Index** & \multicolumn{3}{c}{**Comparison with RS**} & \multicolumn{3}{c}{**Comparison with GNSS**} \\ \cline{3-8}
**Value** & **RMS** & **Bias** & **MAE** & **RMS** & **Bias** & **MAE** \\ \hline Mean & 4.46 & 0.56 & 3.61 & 4.61 & \(-\)0.33 & 3.79 \\ Max & 9.26 & 1.56 & 8.03 & 11.38 & 5.91 & 8.71 \\ Min & 0.98 & \(-\)0.42 & 0.78 & 2.00 & \(-\)8.71 & 1.57 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Statistical results of RMS, Bias, MAE of PWV differences between FY3-A and GNSS (260)/RS (87), respectively, in China over the period of 2012 to 2013. Figure 6: RMS and Bias distributions of PWV differences derived from ERA5 and GNSS/RS over the period of 2012–2020. In addition, the GNSS and RS-derived PWV data were used and interpolated with the same spatial resolution of FY-3A/MERSI using the Delaunay method [51] to verify further the spatial accuracy of FY-3A/MERSI-derived PWV in each season. Figure 8 presents the averaged PWV distribution of FY-3A/MERSI, GNSS and RS and their residuals in four seasons over the period of 2012 to 2013. It can be observed that the PWV product of FY-3A/MERSI is missing in some regions, especially in the southeast of China, which is explained by many clouds in coastal areas. The PWV product with clouds is removed because of its inaccuracy [9]. Furthermore, the accuracy of PWV derived from FY-3A/MERSI is low in summer and autumn with a high PWV value, whereas the accuracy of that is relatively high in spring and winter with a low PWV value. Moreover, the PWV values derived from FY-3A/MERSI is smaller than that from GNSS/RS in summer and autumn, but the values are similar except for the southeast of China in spring and winter. Given the relatively high precision of PWV derived from Sentinel-3A/OLCI [21], only station-based PWV was analyzed between Sentinel-3A/OLCI and GNSS/RS in China from 1 March 2019 to 4 March 2020. The PWV data of Sentinel-3A/OLCI at GNSS and RS stations were first obtained by averaging the gridded PWV data, with a range of 66 pixel nearby the GNSS/RS station [52]. In terms of time matching, the data for Sentinel-3A/OLCI are changed to match the mean of the hour to the GNSS hour data. Figure 9 gives the RMS and Bias distributions of PWV difference between Sentinel-3A/OLCI and GNSS/RS in China from March 1 2019 to March 4 2020. The accuracy of Sentinel-3A/OLCI is high over the whole of China except for several stations.