## 4 Discussion  
This research highlights and certifies critical issues in the detection of high-altitude precipitation that were previously only assumed to be possible. In particular, there is a difference between rain gauge data and IMERG satellite data; in the case of MB and MP, satellite data is significantly higher, while in the case of PB the satellite data is similar to the rain gauge data. In this research, we did not assume that rain gauges are reliable after appropriate data quality control procedures and useful for calibrating IMERG data [26; 27], but tried to assess the weaknesses of both IMERG and rain gauge methods. As a first step, it was decided to analyse the snowfall measured by the snow level sensors of the three weather stations studied, which revealed a serious underestimation of snowfall for satellite data and rain gauges. MB and MP have an underestimation of the snow amount compared to IMERG data of 13.4 and 15.6%, while compared to the rain gauge, there is a difference of 21.6 and 23.7%, respectively. On the other hand, Pintura di Bolognola has an underestimation of the snow amount of 11.2% for the IMERG data, while it is only 6.6% for the rain gauge. A certain degree of underestimation of rain gauges in the case of snowfall in high mountains is an established fact [28], and the underestimation percentages identified in this research are in agreement with what has been observed, for example, in northern Italy, in the Alps [29]. As explained in the results, the water/ snow equivalent ratio was estimated based on existing literature, which may vary the rates of increase, but not substantially. It is significant to note that the errors in snow detection are about 8% higher for rain gauges than for satellite data in the case of MB and MP, while this result is reversed in the case of the PB weather station (6% higher error for IMERG). The IMERG estimation error is often observed in coastal and mountain environments [26], in particular in the latter there is a tendency to underestimate precipitation [30; 31], and this is further confirmation of the extremely significant underestimation of the MB and MP rain gauges; while the PB weather station is in line with the satellite data, probably due to a lower elevation than the other two, which limits its underestimation [32]. Subsequently, anemometric data were studied in an attempt to explain the important differences observed in precipitation between rain gauge and satellite data. The research evaluated the amount of precipitation detected by both the satellite and the rain gauge at certain wind speeds. This analysis showed a similar pattern in the difference in precipitation between IMERG and rain gauge data. The trend showed a growth in precipitation above 5 m/s for the satellite data, while this growth was not found in the case of the rain gauge data, which was more pronounced for MB and PB and less pronounced for MP. This lack of precipitation at high wind speeds for rain gauges can certainly be due to snow blowing or the splashing of rain drops [3; 4; 33]. At the same time, the location of the different weather stations was also assessed, and this showed that weather stations where precipitation does not increase above 5 m/s wind speed have very close peaks that produce a shielding in some wind direction, leading to problems in rain gauge detection. An important component is left out of the analysis, namely the local atmospheric circulation, which through further analysis could provide additional information on prevailing winds not explained by the topography of the area. Finally, as further evidence of the underestimation that occurs in mountain rain gauges, an interpolation was made, taking into account weather stations with an altitude below 1400 m a.s.l. The topographic parameters of the weather stations were employed as independent variables in the multiple linear regression, backward elimination technique [1; 34].