In the present study two extreme events that occurred in the East Coast of Northeast Brazil (ENEB) during 2022 and 2023 were evaluated. These events are becoming increasingly frequent in all regions of Brazil, associated with significant material and human losses, emphasizing the significance of a deeper comprehension of these events. ERA5 global reanalysis data, GOES-16 satellite imagery and pluviometric stations were used for the analysis. Model simulations were also conducted using the Model for Prediction Across Scales (MPAS) with variable resolution (60–3 km). Both events corresponded to Easterly Wave Disturbances (EWDs) that occurred under opposite large-scale conditions of the ENSO cycle, since extreme events are becoming increasingly frequent in all regions of Brazil and could be responsible for significant material and human losses. Thus, an emphasis was given to characterize the synoptic conditions. Both analyzed cases occurred along the ENEB, specifically over the Alagoas state. The trough axis penetrating the studied area was observed on both examined dates, with a very characteristic relative vorticity of this tropical disturbance. In general, moisture convergence resulted from the high flow of moisture prevailing over the region combined with upward movements caused by the trough present at low levels, which combined with local factors in the region such as topography, contributed to the increase in rainfall over the study area in both analyzed cases. The MPAS showed excellent spatial representation when compared to station data, highlighting intense precipitation over parts of Alagoas. •The study highlights the impacts of the Easterly Waves under different configurations of ocean-atmosphere conditions.•Local factors such as topography could contribute to the increase in rainfall values in the study area.•This is the first study to use the MPAS model to simulate extreme precipitation events over the NEB.•MPAS simulations was able to simulate both the spatial distribution and the intensity of the observed precipitation.