## 4 Conclusions  
The main objectives of this study were to describe events of extreme precipitation that resulted in disasters of natural origin in Brazil, identifying whether they were associated with mesoscale convective systems (MCS) and to analyze the performance of various Satellite Precipitation Products (SPP) in detecting the occurrence and magnitude of these extreme rain events. We analyzed extreme events in five regions of Brazil between 2012 and 2016. We identified the date with the heaviest rainfall in the highest number of grid points (>P99 th). The extreme rain event was defined as the accumulated rainfall over five consecutive days, two days before and two days after the date with the highest rainfall. We used INPE's dataset of rain gauges as a reference. We described these extreme events using newspaper reports with photographic records and official civil defense documents that quantitatively report the damage in the affected municipalities. The description of these events highlights the potential of extreme rain to cause great damage, regardless of the area where the event occurs. We found heterogeneity in the details provided by civil defense reports, probably related to the heterogeneous impact of these extreme events in different regions. For example, R1 is characterized by several episodes of severe storms causing substantial damage to affected municipalities. It is easy to find official civil defense documents reporting the phenomenon and estimates of losses associated with the event. In contrast, extreme rain events are less frequent in the semi-arid R3 region of Brazil, and it was impossible to find official civil defense documents quantitatively reporting the event. We showed that all regions of Brazil are prone to natural disasters caused by extreme rains. Although rainfall accumulations have different magnitudes and intensities, extreme  
Figure 22: Bar graphs of (**a**) Probability Of Detection (POD); (**b**) Miss Rate (MR); (**c**) False Alarm Ratio (FAR); (**d**) Threat Score (TS); (**e**) Frequency Bias Index (FBI); and (**f**) Proportion Correct (PC) for five days of accumulated precipitation over the north region of Brazil from 29 April 2016 to 3 May 2016.  
events affect a large proportion of the population. Vulnerability to these types of extreme events should be taken into consideration by public authorities and decision-makers. Several meteorological systems are capable of causing rain in a given region. In this work, we gave special attention to the MCS, systems formed from deep convection and often responsible for severe storms. We showed that the occurrence of MCS and their contribution to extreme rain events in the analyzed cases showed substantial heterogeneities depending on the region. We found that MCS were strongly associated with the extreme rain event in R1; and MCS were present over the five days of the extreme event in the region. We also found a positive relationship between the MCS and the rain event in R2; we found that the highest rain values occurred with many MCS records. Where the amount of accumulated precipitation during the event was lower, the number of MCS was also lower. We found different results in the R3 and R4 regions in northeastern Brazil. The contribution of MCS existed in some grid points with high accumulated rain values, but the association was not as robust as in the other regions. This finding suggests that the extreme rain that occurred during the events was influenced by shallow convective systems or stratiform systems that are not identified by the MCS tracking algorithm used in this work. The R5 region also had a marked influence from the MCS during the event analyzed. To identify the capacity to detect extreme precipitation events in specific cases, we compared extreme precipitation values from 11 different satellite products and rain gauge data in five regions of Brazil. For this purpose, we computed categorical statistics such as (A), (B), (C), (D), (POD), (MR), (FAR), (TS), (FBI), and (PC).