The integration of precipitation estimates from radar and satellite with raingauge data has become more necessary to improve the rainfall information for southern Brazil, where the agricultural sector has major importance, and one of the world-hugest electric power plant installed in this region depend on the hydrological resources with the need of even more accurate information. Currently, the precipitation monitoring has been done by a network of hydrometeorological automatic stations providing very good intensity estimates, but they lack spatial representativeness because of their punctual features. Considering the necessity of providing better products to agriculture and energy sectors of the society, there was a motivation to improve the precipitation information integrating satellite, radar and gauge data. With this purpose, a validation of hourly satellite-derived precipitation estimates from CMORPH and QMORPH techniques has been done, in order to understand their performance during different rainfall events caused by frontal systems, squall lines and convective systems and their behavior during extreme and non-extreme precipitation events. Results from this validation indicate that these estimates capture the mean diurnal cycle very well, but they overestimate precipitation most of the time. The spatial mean BIAS indicates that rainfall is overestimated in almost the whole region during the entire year. In the coastal area, nevertheless precipitation is underestimated mainly during the wettest season (October to March). The efficiency increases for rainfall events with large spatial coverage while decreases for isolated intense cases. Once satellite validation has finished, the technique with the best performance will be used in the integrated precipitation system.