## 2 Materials and Methods
### Hydrological Models
#### 2.4.2 MUSA Model  
The MUSA model represents an effort towards a more accurate representation of the SM and its impact on the modeling of weather systems [25]. Sensitivity tests of precipitation to soil type and soil moisture changes are carried out using the atmospheric Eta model for the numerical simulation of the development of a mesoscale convective system over Northern Argentina. Modified initial soil moisture conditions were obtained from a hydrological balance model developed and running operationally at \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**CEMADEN Stations** & **Latitude** & **Longitude** & \multicolumn{2}{c|}{**SMOS**} & \multicolumn{2}{c}{**LISFLOOD**} \\ \cline{3-6}  & & & ** Asc** & **Des** & ** Asc** & **Des** \\ \hline Abaira & -13.26 & -41.66 & 0.65 & 0.58 & 0.57 & **0.44** \\ Andarai & -12.59 & -41.01 & 0.75 & 0.72 & 0.7 & 0.59 \\ Aracatu & -14.45 & -41.45 & 0.75 & 0.52 & 0.63 & 0.52 \\ Barro Alto & -11.81 & -41.90 & 0.61 & 0.51 & 0.59 & 0.53 \\ Bom Jesus da Serra & -14.38 & -40.49 & 0.65 & 0.55 & 0.5 & **0.39** \\ Brejoes & -13.10 & -39.79 & **0.47** & **0.37** & **0.43** & **0.44** \\ Cabecieras do Paraguacu & -12.62 & -39.23 & **0.49** & **0.44** & 0.5 & 0.52 \\ Caldeirao Grande & -11.05 & -40.15 & 0.57 & **0.31** & **0.33** & **0.31** \\ Caldido Sales & -15.51 & -41.15 & 0.72 & 0.62 & **0.41** & **0.36** \\ Castro Alves & -12.75 & -39.44 & 0.53 & **0.48** & **0.31** & **0.3** \\ Dom Basilio & -13.75 & -41.77 & 0.64 & 0.53 & 0.65 & **0.46** \\ Ibicoara & -13.45 & -41.30 & 0.74 & 0.59 & 0.51 & **0.41** \\ Ipecaeta & -12.29 & -39.32 & 0.52 & **0.40** & **0.39** & **0.24** \\ Itaeté & -13.03 & -40.96 & 0.63 & 0.59 & 0.61 & 0.53 \\ Jeremoabo & -10.00 & -38.33 & **0.15** & **0.1** & **0.15** & **0.11** \\ Jussara & -10.96 & -41.94 & 0.69 & 0.59 & 0.69 & 0.59 \\ Lajedo do Tabocal & -13.43 & -40.24 & **0.49** & **0.36** & **0.37** & **0.32** \\ Lamarão & -11.82 & -38.87 & **0.3** & **0.4** & **0.38** & **0.42** \\ Mundo Novo & -11.86 & -40.48 & 0.5 & 0.5 & 0.51 & 0.53 \\ Canarana & -14.66 & -40.27 & **0.49** & **0.39** & **0.37** & **0.29** \\ Nova Itarana & -13.00 & -40.01 & **0.36** & **0.34** & **0.35** & **0.2** \\ Palmeiras & -12.52 & -41.57 & 0.55 & 0.56 & **0.49** & **0.41** \\ Piripá & -15.01 & -41.74 & **0.08** & **0.1** & **0.17** & **0.2** \\ Planalto & -14.60 & -40.48 & 0.73 & 0.66 & **0.28** & 0.66 \\ São Gabriel & -11.22 & -41.90 & 0.5 & 0.53 & **0.37** & **0.3** \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Correlation between CEMADEM stations SM at 10 cm and SMOS L4 SM and LISFLOOD model at the ascending or descending satellite passes. In boldface: stations with correlation smaller than 0.5. INPE (National Institute for Space Research, Brazil). A new soil map was elaborated using the available soil profile information from Brazil, Paraguay, Uruguay, and Argentina, and it depicts 18 different soil types. Results indicate that the use of more accurate initial soil moisture conditions and incorporating a new soil map with hydraulic parameters, more representative of South American soils, improve the daily total precipitation forecasts both in quantitative and spatial representations [26]. The spatial resolution of the MUSA is 25 km, with daily information. Figures 8 and 9 shows the spatial distribution of the soil moisture obtained from MUSA model for representative years of the droughts in the Brazilian Semiarid region, and for a specific year (2015) within a dry period, respectively. Figure 10 shows the distribution of space-time estimated water storage in soil (mm) for the entire Brazilian territory during the period of 2015 and the TDS-1 passes. Results show that the amount of moisture stored in the soil was lower than the one observed in other years for the NEB, as highlighted in [22]. Figure 8: Yearly average spatial-temporal distribution of the soil water storage [mm] derived from MUSA model at 1 m depth in the Brazilian semiarid during representative years 2010 to 2015.