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

Abstract

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.

Evaluation of the Performance of SM2RAIN-Derived Rainfall Products over Brazil

“…Paredes-Trejo et al [30] showed that for the NEB, this product provides the best performance in terms of Pearson correlations over the Cerrado biome, but fails in the estimation of the amount of rainfall under extreme moisture conditions. Souto et al [42] presented similar results for the São Francisco River basin in Brazil.…”

“…Larger biases in these SPPs were evident over inland northeast Brazil and on the eastern part of the Chapada Diamantina and Serra do Espinhaço cordilleras, in particular for SM2RAIN-ASCAT in summer and autumn (Figure 6j-l). In these regions, the impact of topographic complexity (see Figure 1c) and volume scattering in dry soils [71] on soil moisture retrieval accuracy has been well documented and extensively analyzed in the literature [42,[85][86][87]. A factor less evident that influenced the numerical performance of both SM2RAIN-based products in term of bias is linked to the fact that the rainfall in summer is characterized by intense and short rainfall events (excepting the PMP biome) [88].…”

Reliability of SM2RAIN precipitation datasets in comparison to gauge observations and hydrological modelling over arid regions

“…Despite the interest of the product developers (Brocca et al, 2019), the SM2RAIN P-datasets reliability has only been systematically reported in India (Prakash, 2019), Brazil (Paredes-Trejo et al, 2019;Souto et al, 2019), Pakistan (Rahman et al, 2019), West Africa (Satgé et al, 2020), Austria (Sharifi et al, 2019) and China (Zhang et al, 2019). These studies used precipitation gauge observations as a reference to assess the potential benefits of the SM2RAIN P-datasets ('bottom-up' approach) compared to well-established state-of-the art SPPs.…”

Long‐term meteorological drought characterization in the São Francisco watershed, Brazil: A climatic water balance approach

“…Similarly, Souto et al . (2019) reported that approximately 69.0% of the SFW extension presents a decreasing trend in annual rainfall, although no statistical significance was found. Additionally, Mutti et al .…”