## 3 Comparative Analyses Results
### CMORPH Products  
The precipitation accumulations estimated for both case studies by CMORPH-RT and CMORPH are shown in Figures 13a,b and 14a,b (Table 1 resumes the products features). The identification of the high-density precipitation patterns was similar for both products for both case studies. The differences appear when we compare the \"pixelated\" aspect of CMORPH-RT precipitation patterns (such as over the JUR area) to the smoother aspect of CMORPH during the April case (Figures 13a and 14a, respectively). CMORPH-RT identified more intense precipitation patterns over JUR, the north of the Alps and the southwestern parts of France than CMORPH for the April case. However, CMORPH-RT estimated a less intense precipitation band for the June event than CMORPH (see Figures 13b and 14b). The representation of precipitation patterns was similar with the two products for the April case (Figures 13a,c and 14a,c), but differences in quantification were observed locally. Over the WMC area, CMORPH-RT (Figure 13a) located the high-intensity precipitating cells outside the area, with a southwest shift. In comparison, the position of the most-intense precipitation amounts estimated by CMORPH (Figure 14a) was located close to RADOME's maximum over the WMC area. Close to the JUR area, CMORPH-RT showed pixel clusters with very-low-intensity precipitation amounts adjacent to moderate- to high-intensity precipitating cells not observed with RADOME (Figure 2a). CMORPH represents the precipitation pattern over this area with a much smoother appearance. We can see high-intensity estimations over the northern parts of the Alps. However, very-low-intensity precipitation amounts over the SAL and DUR areas were identified by both products, revealing a northern spatial shift over the Alps. Table 2 confirms the shifted location of the precipitation accumulation maximum of CMORPH-RT compared to the RADOME counterparts. However, we can note that the CMORPH maximums were closer to RADOME ones than CMORPH-RT, with the only exception being the JUR area. By looking at the spatial bias distribution (Figures 13c and 14c), we can see a large underestimation trend across the Southern parts of the country for both products, especially over the SAL, DUR, and WMC. This trend is confirmed when we see the negative biases computed over these areas (Table 3). However, over the JUR area, we can note that CMORPH-RT estimations overestimated RADOME by +12.84 mm on average, while for CMORPH the average difference was close to 0 mm. Figure 13: As in Figure 4, but for rain accumulations estimated by the CMORPH-RT product. The June case (Figures 13b,d and 14b,d) was extended from the NMC area to the northeast of the country for both products. The main difference was in the quantification of the event, as CMORPH-RT estimated a small area of moderate precipitation intensity (less than 60 mm), while CMORPH estimated higher precipitation amounts closer to the RADOME observations. As seen in Table 2, the maximum estimated by CMORPH-RT was around 2 times lower than the RADOME maximum over NMC, whereas CMORPH had a similar maximum compared to the RADOME counterpart. However, this CMORPH maximum was located 83.22 km to the east of the Chastreix station against the 46.20 km separating Chastreix to the CMORPH-RT maximum. In Figure 13d and Table 3, we can see the strong underestimation trend observed with CMORPH-RT over the NMC and France. In contrast, CMORPH (Figure 14d) overestimated at locations around the centre of the NMC area, leading to a slight positive bias on average (+1.25 mm). The rainfall patterns estimated by the two CMORPH versions present some differences at the local scale. CMORPH-RT estimations were highly heterogeneous in some areas such as JUR during the April event. CMORPH-RT is a real-time product and has to wait for the next PMW estimation from the satellite flyby to update its estimations [47].