Performance of Remotely Sensed Soil Moisture for Temporal and Spatial Analysis of Rainfall over São Francisco River Basin, Brazil
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 precipita...
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doaj-c3641fca32a5477d906b6b9affb48ed72020-11-25T00:52:34ZengMDPI AGGeosciences2076-32632019-03-019314410.3390/geosciences9030144geosciences9030144Performance of Remotely Sensed Soil Moisture for Temporal and Spatial Analysis of Rainfall over São Francisco River Basin, BrazilJefferson Souto0Norma Beltrão1Ana Teodoro2Postgraduate Program in Environmental Sciences, State University of Pará (UEPA), Belém 66095-100, BrazilPostgraduate Program in Environmental Sciences, State University of Pará (UEPA), Belém 66095-100, BrazilEarth Sciences Institute (ICT) and Faculty of Sciences (FCUP), University of Porto, 4169-007 Porto, PortugalVariability 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.https://www.mdpi.com/2076-3263/9/3/144rainfallsoil moistureSM2RAINremote sensing |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Jefferson Souto Norma Beltrão Ana Teodoro |
spellingShingle |
Jefferson Souto Norma Beltrão Ana Teodoro Performance of Remotely Sensed Soil Moisture for Temporal and Spatial Analysis of Rainfall over São Francisco River Basin, Brazil Geosciences rainfall soil moisture SM2RAIN remote sensing |
author_facet |
Jefferson Souto Norma Beltrão Ana Teodoro |
author_sort |
Jefferson Souto |
title |
Performance of Remotely Sensed Soil Moisture for Temporal and Spatial Analysis of Rainfall over São Francisco River Basin, Brazil |
title_short |
Performance of Remotely Sensed Soil Moisture for Temporal and Spatial Analysis of Rainfall over São Francisco River Basin, Brazil |
title_full |
Performance of Remotely Sensed Soil Moisture for Temporal and Spatial Analysis of Rainfall over São Francisco River Basin, Brazil |
title_fullStr |
Performance of Remotely Sensed Soil Moisture for Temporal and Spatial Analysis of Rainfall over São Francisco River Basin, Brazil |
title_full_unstemmed |
Performance of Remotely Sensed Soil Moisture for Temporal and Spatial Analysis of Rainfall over São Francisco River Basin, Brazil |
title_sort |
performance of remotely sensed soil moisture for temporal and spatial analysis of rainfall over são francisco river basin, brazil |
publisher |
MDPI AG |
series |
Geosciences |
issn |
2076-3263 |
publishDate |
2019-03-01 |
description |
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. |
topic |
rainfall soil moisture SM2RAIN remote sensing |
url |
https://www.mdpi.com/2076-3263/9/3/144 |
work_keys_str_mv |
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