The Brazilian Northeast (BNE) is located in the tropical region of Brazil. It is bounded by the Atlantic Ocean, and its climate and vegetation are strongly affected by continental plateaus. The plateaus keep the humid air masses to the east and are responsible for the rain episodes, and at the west side the northeastern hinterland and dry air masses are observed. This work is a case study that aims to evaluate the impact of updating the model initial condition using the 3DEnVar (Three-Dimensional Ensemble Variational) system in heavy rain episodes associated with Mesoscale Convective Systems (MCS). The results were compared to 3DVar (Three-Dimensional Variational) and EnSRF (Ensemble Square Root Filter) systems and with no data assimilation. The study enclosed two MCS cases occurring on 14 and 24 January 2017. For that purpose, the RMS (Regional Modeling System) version 3.0.0, maintained by the Center for Weather Forecasting and Climate Studies (CPTEC), used two components: the Weather Research and Forecasting (WRF) mesoscale model and the GSI (Gridpoint Statistical Interpolation) data assimilation system. Currently, the RMS provides the WRF initial conditions by using 3DVar data assimilation methodology. The 3DVar uses a climatological covariance matrix to minimize model errors. In this work, the 3DEnVar updates the RMS climatological covariance matrix through the forecast members based on the errors of the day. This work evaluated the improvements in the detection and estimation of 24 h accumulated precipitation in MCS events. The statistic index RMSE (Root Mean Square Error) showed that the hybrid data assimilation system (3DEnVar) performed better in reproducing the precipitation in the MCS occurred on 14 January 2017. On 24 January 2017, the EnSRF was the best system for improving the WRF forecast. In general, the BIAS showed that the WRF initialized with different initial conditions overestimated the 24 h accumulated precipitation. Therefore, the viability of using a hybrid system may depend on the hybrid algorithm that can modify the weights attributed to the EnSRF and 3DVar matrix in the GSI over the assimilation cycles.

This study evaluated the relationship between different surface hydrometeorological variables and rainfall during the wet period of the South American Monsoon System (SAMS). A climatological study was performed for 30 rainy periods of the SAMS between the years 1991–2021 over the Central-West region of Brazil (WCB) (20–10° S and 60–50° W). The European Centre for Medium-Range Weather Forecasts Reanalysis 5th/ERA5 was used to understand, under different soil moist conditions (dry, intermediate, and wet), the hydrometeorological patterns and their impacts on SAMS during the three stages of the wet period: the development (September-October-November, SON), maturity (December-January-February, DJF), and weakening (March-April-May, MAM) South American monsoon quarters. The results show that along with an increase (decrease) in rainfall during the rainy season, there is also a significant increase (decrease) in both surface and subsurface volumetric soil moisture (θ) for the wet (dry) soil condition periods. However, the surface heat flux composites showed that the latent heat fluxes to the atmosphere (H_l) significantly exceeds the climatology during the SAMS development quarters (SON) for the wet soil group. In contrast, for the dry soil group, the significant increase of H_l, compared to the climatology, over the WCB occurred only during the SAMS maturity quarters (DJF), representing, in this last case, a significant injection of latent heat and consequently delayed evaporation (EV P) compared to rainy periods with wet soil, due to the low soil moisture content and the prevalence of dry convection over WCB. Regarding the sensible heat fluxes (H_s), it was observed drier (wetter) soils tend to exhibit values above (below) the climatological mean throughout all stages of SAMS evolution over the WCB. The 2-m air temperature (T 2m) and planetary boundary layer height (P BLH) anomaly composites showed that for the wet (dry) soil group and with significant rainfall above (below) the climatological mean over the WCB, all evolution quarters were marked by a significant decrease (increase) in T 2m and P BLH anomalies. Regarding the mechanisms of direct feedback between surface variables and rainfall associated with the SAMS, significant direct correlations were also observed between the mean rainfall of the SAMS rainy season and the mean values of active days duration (D_ad), H_l, H_s and the surface Soil Moisture Condition Index (SMCI₁).