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The Amazon basin, with a drainage area of about 6 million km2, is the largest drainage basin in the world, consequently the accurate measuring the rainfall dynamics at high spatial and temporal resolution is essential for a better understanding of the hydrological cycle. So, we validated rainfall estimates from the Tropical Rainfall Measuring Mission (TRMM) satellite using surface precipitation data collected from 2004 to 2012. Rainfall data came from the Jaru Biological Reserve meteorological station, located to the east in the state of Rondônia, Brazil, and was compared with the estimates of the algorithms 3B42 V7 and 3B43 V7 of the product TRMM. Statistical analysis was based on indices of continuous variables such as the Spearman correlation coefficient (ρ), the square root mean square error normalized by the mean of the observed values (NRMSE), the mean square error (RMSE), the error (ERV) and some categorical indices such as probability of detection (POD), False Alarm (FAR) and critical success rate (CSI) between the daily and monthly precipitation observed data and the estimated precipitation data. The 3B43 V7 precipitation estimates were broadly representative of surface observations, but underestimated precipitation in the wet season and overestimated precipitation in the dry season. The 3B42 V7 product performed poorly and does not generate a robust representation of surface precipitation.

Estimation of rainfall based on remote sensing and observation fields in Jaru Biological Reserve at the Brazilian Amazonian forest