## 3 Results and Discussion
### Case Study for the Central Region--R2  
In the central region of Brazil (R2), extreme rains between 1 January 2012 and 5 January 2012 affected several municipalities in Rio de Janeiro, Espirito Santo, and Minas Gerais; a public calamity was officially declared. According to a Civil Defence report, more than 200 thousand people were affected, and the estimated economic damage was greater than US$ 4 million. The human, material, and environmental damage was enormous, with blocked roads, collapsing ravines, and floods recorded in various places. Figure 7 illustrates some of this damage in some affected municipalities. The results suggest that the MCS had a large influence perceived in the extreme event studied in the central region (R2), 1 January 2012 to 5 January 2012 (Figure 8). The ratio between the rain on the days when there was an MCS and the cumulative rain in those five days was above 80% (Figure 8b) in Rio de Janeiro and south of Minas Gerais, which had the highest accumulated rainfall (\(\geq\)140 mm/5 days) (Figure 8a). In areas where the accumulated rainfall was lower, MCS seemed less relevant (\(\leq\)50%) (Figure 8b). Figure 8c shows the number of MCS events recorded by the TOOCAN algorithm in the five days analyzed. The most affected area in the region had over 25 MCS during this extreme rainfall event. The fraction of time occupied by the MCS varied between 10% and 100% (Figure 8d). One possible explanation for this large observed variation was the presence of persistent stratiform clouds, in addition to convective clouds, due to the influence of the SACZ system. This system is characterized by a persistent band of clouds oriented northwest-southeast, extending from the Amazon basin to the southwest of the Atlantic  
Figure 6: 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 south region of Brazil from 24 June 2014 to 28 June 2014. Ocean [28; 52]. Furthermore, a cyclone in the Atlantic Ocean caused winds from the south along the coast of Rio de Janeiro and Esprito Santo, favoring convergence at low levels. Figure 8: **(a)** Accumulated rainfall recorded from 1 January 2012 to 5 January 2012 over the central region of Brazil (R2); **(b)** fraction of rain on days that had MCS record 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 7: Municipalities affected by the extreme rain. **(a)** flooding in municipality of Muriaé on Minas Gerais state; **(b)** collapse of houses in municipality of Duque de Caxias on Rio de Janeiro state. Photographs: [PERSON]/VC no G1 and [PERSON]/ABr/exame.com. Figure 9 shows the spatial distribution of extreme rainfall estimated over five days. The rainy area occupied a large extension during the studied period, from the southeast to the northwest of Brazil, with the heaviest rain occurring over the states of Rio de Janeiro, Espirito Santo, and Minas Gerais. All the products analyzed were able to spatially identify the rain distribution; however, only products 3B42g, COSCHg, and TAPEER (Figure 9f,i,l, respectively) presented a similar spatial distribution to the reference data (Figure 9m). The others products underestimated the rain intensity (\(\geq\)40 mm). These results were confirmed using categorical indices (Figure 10). [PERSON] et al. [53] observed similar results when evaluating 3B42 estimates. Those authors found that the product could correctly represent the five days of accumulated precipitation in the northeastern region of Brazil (PC \(>\) 0.7); however, it underestimated the precipitation observed by the rain gauge. The indices suggest that 3B42g, COSCHg, and TAPEER were closer to the reference data, as they present a smaller error with FBI values closer to the perfect score.