## 3 Results and Discussion
### Case Study for North Brazil--R5  
An extreme rain event occurred between 29 April 2016 and 3 May 2016 in the north region of Brazil. Heavy rain during these five days wreaked havoc in several neighborhoods in the municipality of Monte Alegre in western Para (Figure 19), registering about 130 mm of rain in a single day. As a municipality with rugged topography, steep slopes favored sudden floods in urban areas, heavily affecting the local population. The Civil Defence disaster report estimated that about 145 people were left homeless, 130 people were displaced, and 15,265 people were negatively affected by these extreme rains. Seven neighborhoods in the urban area were affected, including eight houses destroyed, 42 homes severely damaged, and 2700 houses were isolated because of damage to bridges and road networks. Other public infrastructure was also damaged or destroyed, including schools, health centers, daycares, water supply systems, and energy infrastructure. The National System of Protection and Civil Defence (SINPDEC) estimated an approximate cost of 0.58 million USD to restore damage to public infrastructure, remove debris and garbage, and restore services. Damage was greater in the private sector, with an estimated loss of about 0.87 million USD from commerce, agriculture, and business losses. Unfortunately, the frequency of extreme precipitation events is increasing in the region, putting many people in the way of danger [58]. Figure 17: Case of extreme precipitation occurred over northeast coast of Brazil (R4) from 14 April 2016 to 18 April 2016 estimated by different products (**a**-**m**). Figure 19: One of the municipalities affected by the extreme rain. (**a**) and (**b**) collapse of houses in municipality of Monte Alegre in Pará state. Photographs: [PERSON]/G1 and Reproducão/TV Tapajós). Figure 18: 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 northeast coast region of Brazil during 14 April 2016 to 18 April 2016. Figure 20 shows the influence of the MCS on this case of extreme rain in R5. A large influence of MCS was found for grid points that presented high (\(\geq\)140 mm/5 days) and low accumulated rainfall (between 10 mm/5 days and 40 mm/5 days) (Figure 20a,b). The number of MCS varied from 5 to 30, and the fraction of the time occupied by MCS varied from 40% to 100% (Figure 20c,d). The areas to the east of R5 recorded low amounts of accumulated rain (between 10 to 40 mm/5 days), with precipitation heavily influenced by the MCS (100%), a high number of MCS registered by grid point (10-25), and a high fraction of time occupied by the MCS (80% to 100%). In contrast, areas west of R5, which registered low values of accumulated rain (between 10 and 40 mm/5 days), presented substantial variation in MCS contribution values, varying between 30% and 100%, with fewer MCS registered (10-15), and a smaller fraction of time occupied by MCS (between 40% and 80%). Figure 21 shows the spatial distribution of this precipitation event from different satellite products. Grid points with the highest rain were located at the center of Para state and north of Amapa state (Figure 21m). The categorical indexes for extreme rain in R5 suggest that COSCHg had the best performance (Figure 21i), with scores close to perfect for POD, MR, FAR, TS, FBI, and PC (Figure 22). Nevertheless, all products underestimated the rain, considering the FBI \(\leq\)1. The products with the highest false alarm and Miss Rate, and thus the lowest POD, were the 3B42 and the CMORPH. COSCHg did better than other products in R5, presenting a low FAR (0.0), high POD (0.55), and a high PC (0.94).