## 3 Results and Discussion
### Case Study for Northeast Coast--R4  
The largest case of extreme rain in the Northeast Coast (R4) occurred from 14 April 2016 to 18 April 2016. According to a report by the Civil Defence, about 568 people were directly affected by the floods and landslides, and 1700 were left without electricity. For example, the volume of rain recorded in the city of Joao Pessoa-PB (Figure 15) was about 20% higher than historically expected for the month of April in this region. More than 200 mm of rainfall were recorded during the five days analyzed. The average historic rainfall volume is around 250 mm for the entire month [30]. [PERSON] et al. [54] and [PERSON] et al. [57] identified, respectively, through satellite data and rain gauges, that April is among the months with the highest rainfall intensities on the east coast in the Northeast. Those authors show that the probability of an extreme event occurring in a city on the east coast of Northeast Brazil during April is 85.9%.  
Figure 16 represents the influence of the MCS in this case of extreme rain. Figure 16a reveals a large variation of accumulated rainfall in five days between locations (20 mm/5 days to values greater than 140 mm/5 days). The most affected city was Joao Pessoa-PB and its surrounding municipalities, where the grid points with the highest values of accumulated rainfall are verified. Figure 16b shows that the MCS influenced around 80% of registered rain. Areas located north of this municipality recorded less rainfall (between 10 mm/5 days and 60 mm/5 days) but had a more significant contribution from MCS (between 90% and 100%). Areas located south of Joao Pessoa-PB had less accumulated rainfall (between 10 mm/5 days and 60 mm/5 days), with a smaller contribution from the MCS (between 50% and 70%). According to [PERSON] and [PERSON] [42], shallow convective clouds occur more  
Figure 14: 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 Northeastern region of Brazil from 20 January 2016 to 24 January 2016.  
frequently over the ocean and coastal areas of northeast Brazil from March to August. Those authors find that deep convective systems are not frequent in this region but are the main contributor to rain when they occur, consistent with our results. The number of MCS varied considerably in this region, from 5 to 25 MCS per grid point during the five days analyzed (Figure 16c). The time occupied by MCS varied from 80% to 100% in areas north of R4 and from 20% to 60% in areas south of R4.  
Figure 16: (**a**) Accumulated rainfall recorded during 14 April 2016 to 18 April 2016 over northeast coast of Brazil (R4); (**b**) fraction of rain on days that had MCS records over the rain accumulated in five days; (**c**) number of MCS events recorded in five days; (**d**) fraction of the days that had MCS records; (**e**) analyzed region.  
Figure 15: One of the municipalities affected by the extreme rain. (**a**) flooding in Municipality of João Pessoa in Paraiba state; (**b**) collapse of houses in municipality of João Pessoa in Paraiba state. Photograph: [PERSON]/G1 and [PERSON]/G1).  
Figure 17 shows the spatial distribution of this extreme precipitation event based on different satellite products. The grid point with the heaviest rain was located in the coastal region of Paraiba state in the reference dataset (Figure 17m). The precipitation estimate products in this region were very close to the perfect score in categorical indexes, as shown in Figure 18. Products 3B42g, CMORPH, CMORPHg, GSMAP, GSMAPg, PERSIANNg, CHIRP, and COSCHg presented POD = 1, MR = 0, and FAR = 0, showing a good performance in R4. CHIRPg delivered the poorest performance in rain estimation, compared to the other products.