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The east coast of Northeast Brazil (ENEB) has experienced an increase in extreme precipitation events in recent years because of climate change caused by human activities. ENEB is characterized by the influence of several synoptic-scale systems throughout the year that contribute to the development of extreme precipitation events, emphasizing that the region needs actions to increase its capacity to predict the threat of natural hazards with significant material and human losses. Several studies have shown an increase in the frequency and intensity of these events, accenting the growing importance of accurate numerical weather prediction models has become increasingly critical in aiding decision-makers and governments to plan effective actions that can prevent or mitigate catastrophic consequences. In the present study, one extreme precipitation event developed over the Alagoas state (located at the ENEB) occurred in July 01, 2022 was analyzed. The accumulated rainfall of 185 mm/day was recorded, triggering landslides, floods and river overflows in different cities. The main objective of this study was to apply the Model for Prediction Across Scales Atmosphere (MPAS) model with a variable-resolution mesh to perform the simulation for both extreme precipitation events. A 60-3 km variable resolution mesh with refinement centered on the city of Maceió was configured. The high resolution (3 km) can resolve the known finer-scale mechanisms responsible for cloud formation in the region. Numerical simulations were driven by ERA5 reanalysis to investigate sensitivity to initial conditions. Gridded data from MERGE/CPTEC (0.1°) for hourly accumulated precipitation were used to evaluate the simulated hourly accumulated precipitation. Through the results obtained in the analysis, it was possible to observe a significant variation in the correlations between MPAS and MERGE, with values above 0.67 for some cities affected by heavy rainfall (Quebrangulo, Paulo Jacinto, and Cajueiro), indicating that the model was able to track the temporal variability in these cities. On the other hand, in cities where lower correlations were observed, there might have been some displacement of the rain relative to the observed MERGE data. The BIAS analysis indicated that MPAS tends to underestimate precipitation at all evaluated points, with the highest intensities occurring in locations with higher correlations, suggesting that the model captured the position of the rainfall well but did not accurately represent the volumes. This becomes evident when evaluating the RMSE, MAE, and BIAS, where the values were more pronounced in locations with higher rainfall volumes, reaching up to 7.78 mm/h. These results provide important information into the performance of MPAS, highlighting the need for an extended evaluation with other physical parameterizations and model configurations.

The moisture transport from Amazon forest is a great moisture source for the regional water cycle in South America (SA), especially at southeast and southern part including Parana and La Plata Basins. Several previous studies have shown this importance and how anthropic processes of either global warming and/or Amazon deforestation may affect this Amazonian moisture by the aerial rivers. The new advances in the parameterization of the microphysics (for instance using the convective permitting models) allow improvements in the water representation in varying timescales. So, in order to do this study, we have used 2 data-set from Amazonia: a) the Meteorological Office Unified Model (UM) simulations for 4.5 and 25 km horizontal resolutions; b) the ERA5 reanalysis (vertical profiles of windspeed and specific humidity). The period used in these analysis were from 1998-2007 during the austral summer (months from December up to February). The moisture transport was computed from the surface up to middle troposphere (500 hPa) using IVT definitions. We selected 2 boxs domains: one in the Amazon basin and the other in the Brazilian southeast region (named Sao Paulo) in order to identify the moistures output and input for water budget. The results showed some precipitation bias, mainly in the central/south Amazon basin (~ +2.5 mm.day-1) and in Sao Paulo +1.5 mm.day-1). Some similarities were identified between 4.5 km and observations (ERA5) vertically integrated moisture flow patterns for Amazon basin as well as northern Sao Paulo area (-7% and -13%, respectively). On the other hand, the 25 km simulation underestimated the intensity of fluxes in the whole pathway by 4.5%, which represents -6.9 kg m-1 s-1. The low water transport was explained by some reduction on the vertical moisture transport, mainly between 700 and 500hPa (~ -3.2 kg m-1 s-1 in the Amazon southern area and -2.5 kg m-1 s-1 in Sao Paulo area). Despite some biases identified, the differences compared to ERA5 data are small, indicating that convection-permitting models offer valuable insights for better understanding regional climate connections, albeit their elevated computational costs.

Conhecer o estado atual da atmosfera em diferentes níveis de altitude é fundamental para a melhoria da precisão e confiabilidade das previsões meteorológicas e ajudam a compreender eficazmente os padrões climáticos e fenômenos meteorológicos em todo o mundo (DIRKSEN, et al., 2014). Além de fornecem uma configuração tridimensional da atmosfera, os dados são importantes principalmente para a previsão do tempo operacional (INGLEBY; EDWARDS, 2015).

The mechanisms of NPF involve the interaction of various precursor gases and specific thermodynamic conditions (Olenius et al., 2018). However, the uncertainties associated with these processes, particularly regarding chemical diversity and its transformations, emission sources, and impacts on clouds, lead to significant uncertainty in climate change predictions (Boucheret al., 2013; Tellus B et al., 2021).

In Brazil, some studies have been conducted to evaluate the quality performance of ECMWF reanalysis using statistical methods in areas with sparse observed data coverage, aiming to understand the performance of fields estimated by numerical models in simulating dynamic processes over the surface [1-2]. However, no validation has been accompanied by altitude correction for ECMWF’s fifth-generation reanalysis data until the present study.

The breeze is an important factor in explaining the diurnal wind cycle (Barreto et al., 2002), particularly in coastal regions. As winds move from areas of high to low pressure, diurnal circulation carries winds from the sea to the land (onshore) at lower levels, creating a return current at higher levels, which characterizes the sea breeze. During the night, the reverse process occurs (offshore), known as the land breeze phenomenon.