## 4 Discussion  
In this Section, we further discuss the quantitative agreement among the four precipitation products in the 221 sites where gauge measurements are available; then, we analyze the qualitative agreement among GPM, RADAR, and CombiPrecip in the described study area (\(360\times 240\) km\({}^{2}\)), with special focus on the Swiss territory. We first complete the visualization of the scatterplots associated with the correlation coefficient values that are shown in Table 1 and discussed in Section 3. In this respect, Figure 2 shows the Log-transformed annual precipitation estimates and Figure 3 shows the original linear values. \begin{table}
\begin{tabular}{c c c c} \hline \hline  & **CombiPrecip** & **RADAR** & **GAUGE** \\ \hline Log-transformed total precipitation amounts & 0.628 & 0.547 & 0.403 \\ Total precipitation amounts (linear) & 0.536 & 0.397 & 0.290 \\ Log-transformed total amounts (version V05A) & 0.626 & 0.546 & 0.416 \\ Total amounts (version V05A) & 0.548 & 0.412 & 0.307 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Pearson correlation coefficients between the estimates of the Global Precipitation Measurement radar (versions V04A and V05A) above 221 Swiss sites and the estimates derived from three different MeteoSwiss precipitation products. \begin{table}
\begin{tabular}{c c c c} \hline \hline  & **CombiPrecip** & **RADAR** & **GAUGE** \\ \hline MeteoSwiss products as a reference (GPM V04A) & 2.38 dB & 2.81 dB & 2.84 dB \\ GPM product (V04A) as a reference & 1.86 dB & 2.22 dB & 2.40 dB \\ MeteoSwiss products as a reference (GPM V05A) & 2.43 dB & 2.60 dB & 2.77 dB \\ GPM product (V05A) as a reference & 1.83 dB & 2.20 dB & 2.35 dB \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Scatter in dB between GPM estimates (versions V04A and V05A) above 221 Swiss sites and the estimates derived from three different MeteoSwiss precipitation products. Please note that, with respect to Figure 2, we have changed the independent variable point of view, and thus, in Figure 3, the gauge amounts are reported on the abscissa, while GPM (augmented by 2 dB), RADAR, and CombiPrecip are shown on the ordinate. We have opted for GAUGE values on the abscissa to check the reliability and representativeness of the values corresponding to the large gauge amounts collected every 10 min that were acquired during the first 2 years of activity of the GPM Core Observatory satellite. As stated in Section 2, these 528 samples are synchronous with the GPM overpasses over the Swiss territory and represent a \"random\" subsample of 0.5% of all available samples. Using all samples, the rainiest site (ROE, 1896 m altitude) shows \(\sim\)2500 mm/a, while the second and third rainiest sites (SAE, 2502 m; GSB, 2472 m) show \(\sim\)2350 mm/a and \(\sim\)2150 mm/a, respectively. As can be easily seen in Figures 1 and 2, using the GPM-synchronous 528 samples, the rainiest site is found to be GSB (\(\sim\)3220 mm/a) followed by Saentis (SAE, \(\sim\)2770 mm/a). Figure 2 also shows that while the RADAR and CPC underestimation at the SAE site are still \"acceptable\", at the GSB site they are not. All three products suggest that the rain gauge is not reliable at that site. This fact is well known at MeteoSwiss: for instance, the correlation coefficient between 6589 wet-wet RADAR-GAUGE hourly amounts during the period 2005-2009 is as low as 0.133. Additional investigations have suggested that this rain gauge site is far from being ideal. At the end of 2016, a new rain gauge was installed in a better position (\(\sim\)1 km away from the old site). Preliminary comparisons between the radar and the two gauge estimates seem to confirm that the site of the new gauge is much better. Thanks to GPM (see Figure 2), MeteoSwiss has an additional confirmation of the problem at GSB. It is also worth noting that the correlation and scatter values presented in Section 3 are not sensitive to the GSB data pair; rather, they are reasonably resistant.