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Performance of Remotely Sensed Soil Moisture for Temporal and Spatial Analysis of Rainfall over São Francisco River Basin, Brazil

Postgraduate Program in Environmental Sciences, State University of Pará (UEPA), Belém 66095-100, Brazil
Earth Sciences Institute (ICT) and Faculty of Sciences (FCUP), University of Porto, 4169-007 Porto, Portugal
Author to whom correspondence should be addressed.
Geosciences 2019, 9(3), 144;
Received: 30 January 2019 / Revised: 20 March 2019 / Accepted: 22 March 2019 / Published: 26 March 2019
(This article belongs to the Special Issue Remote Sensing used in Environmental Hydrology)
PDF [4561 KB, uploaded 26 March 2019]


Variability in precipitation patterns in the northeast and southeast regions of Brazil are complex, and the combined effects of the Tropical Atlantic, Pacific Niños, and local characteristics influence the precipitation rates. This study assesses the performance of multi-satellite precipitation product SM2RAIN-Climate Change Initiative (SM2RAIN-CCI) for the period of 1998–2015 at monthly scale. To accomplish this aim, various statistical analyses and comparison of multi-satellite precipitation analysis products with rain gauge stations are carried out. In addition, we used three values corresponding to extreme events: The total daily precipitation (PRCPTOT) and the number of consecutive dry/wet days (CDD/CWD). Results reveal that monthly rainfall data from SM2RAIN-CCI are compatible with surface observations, showing a seasonal pattern typical of the region. Data correlate well with observations for the selected stations (r ≥ 0.85) but tend to overestimate high rainfall values (>80 mm/month) in the rainy area. There is a significant decrease in rainfall to the indices, especially in PRCPTOT during the occurrence of tropical ocean–atmosphere interactions, reflecting CWD and CDD values. Moreover, our findings also indicate a relationship, at interannual timescales, between the state of El Niño Southern-Oscillation (ENSO) and Tropical Atlantic (TA) annual precipitation variability from 1998 to 2015. The SM2RAIN-CCI could be a useful alternative for rain-gauge precipitation data in the São Francisco River basin. View Full-Text
Keywords: rainfall; soil moisture; SM2RAIN; remote sensing rainfall; soil moisture; SM2RAIN; remote sensing

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Souto, J.; Beltrão, N.; Teodoro, A. Performance of Remotely Sensed Soil Moisture for Temporal and Spatial Analysis of Rainfall over São Francisco River Basin, Brazil. Geosciences 2019, 9, 144.

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