###### Abstract  
The number of natural disasters triggered by extreme events is increasing worldwide and significantly impacts modern society. Extreme rainfall is one of the most important factors contributing to these events. A better understanding of the physical process that causes extreme rainfall can allow rapid responses from decision-makers to lessen the impact of natural disasters on the local population. Satellite monitoring is widely used for this purpose and is essential for regions where terrestrial observations are limited or non-existent. The primary purpose of this study is to describe the performance of satellite products for extreme rainfall events that caused natural disasters in various climate regimes in Brazil and discuss the contribution of mesoscale convective systems (MCS) to these events. We defined regions based on the climatological rainfall distribution. Cases with rain values above the 99 th percentile during 2012-2016 were considered statistically extreme. Our analysis is based on three datasets, with precipitation from (i) rain gauge stations, (ii) different satellite-based estimates, and (iii) mesoscale convective tracking data. The methodology was based on identifying extreme rainfall events, analyzing the performance of satellite precipitation estimates and, finally, quantifying the influence of convective systems on extreme rain. Although all regions of Brazil may be affected by natural disasters caused by extreme rains, the results suggest that the impacts caused in each region are different in magnitude. Convective systems explained over 90% of extreme rains in the case analyzed in Brazil's south and about 60% to 90% of extreme rains in the case analyzed in the Northeast. In general, satellite products have identified rain events; however, in the southern region of Brazil, products have tended to overestimate rainfall, while other regions have tended to underestimate extreme rain values. The methods used in satellite precipitation estimation products have limitations to accurately identifying specific extreme rain events. extreme events; precipitation; natural disasters; satellite +
Footnote †: journal:  
00000-0002-4013-1401]D. A.  
report, extreme rainfall events will become more common and intense over the next decades [1]. The IPCC disaster and death information survey from 1970-2008 concluded that over 95% of natural-disaster-related deaths have occurred in low- and middle-income countries. According to the Brazilian Atlas of Natural Disasters, about 40,000 disasters occurred between 1991 and 2012, caused by meteorological, hydrological, and geological events [2]. Unfortunately, these numbers have increased every year, and survey data with more updated information are necessary. Most natural disasters in Brazil are triggered by precipitating meteorological systems [3]. These systems can generate large amounts of rain in a large area over a long period or profuse rain in a smaller area in a few hours. Examples are the South Atlantic convergence zone (SACZ) and the mesoscale convective systems (MCS), respectively [4]. The main types of meteorological systems that occur and the most favorable seasons of the year may vary by region. For example, in the south region of Brazil, frontal systems, cyclones, and MCS are common [5; 6]. In the north and northeast regions of Brazil, the intertropical convergence zone [7], the tropical Squall lines [8], upper-level cyclonic vortex, easterly waves, and sea breeze circulation [9; 10] are more common. Due to the spatial coverage and high spatial/temporal resolutions, satellite data are of fundamental importance in the analysis and understanding of past extreme events to prevent or mitigate disasters that will occur in the near future. Several studies have tried to find the best ways to extract satellite data to improve the performance of precipitation estimates based on satellite precipitation products [11; 12; 13; 14; 15; 16; 17; 18; 19].