The oceanic South Atlantic Convergence Zone (SACZ) has played a major role during South America’s 2021/2022 summer extreme rainy season, being responsible for more than 90% of the precipitation in some regions of Southeast Brazil and in some regions of the Southwestern Atlantic Ocean (SWA). The summer of 2021/2022 was unique and rare and considered an abnormally humid season as verified by official Brazilian Institutes. First, the unusual number of cases of SACZ episodes (seven), was the highest recorded in the last decade. Second, all the cases that occurred were oceanic SACZ that assumed characteristics of an Atmospheric River and produced an excessively anomalous amount of precipitation during this period. Excess precipitation along with the regions located in mountainous and very uneven relief, which by orographic effects favors high precipitation volumes, were responsible for amplifying the observed impacts, such as landslides and floods that caused several losses to society. We also showed the main effects of coupling and interaction between the waters of the surface layer of the SWA and the atmosphere. Our learning from this study ends with the unprecedented results of how the marine atmospheric boundary layer (MABL) is locally modulated by the sea surface temperature (SST) that lies just below it. Until the present moment, we emphasize that this important mechanism has not been widely highlighted in the literature, showing that even though the ocean is colder than before oceanic SACZ is established, it is still warmer than the overlying air, thus, the ocean continues to be an active source of heat and moisture for the atmosphere and enhances the MABL instability process.

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ResumoDevido à relevância do entendimento da influência dos fluxos atmosféricos sobre o estado do oceano, em especial, a modelagem e previsão das interações entre esses dois sistemas, o presente estudo objetivou comparar, climatologicamente, duas reanálises atmosféricas com relação à energia dos ventos sobre a superfície do mar para margem continental leste/sudeste brasileira. Os produtos selecionados foram o Climate Forecast System Reanalysis (CFSR) e o ERA-Interim (ERAI), comparados entre si de 1979 a 2010 e validados de acordo com os dados remotos do Advanced Scatterometer (ASCAT) entre maio/2007 e dezembro/2010. Os resultados demonstraram claro padrão mais energético do CFSR em relação ao ERAI, seja espacial ou temporalmente, exceção feita a certas áreas costeiras. Quantitativamente, o primeiro produto, em média, foi 13% mais intenso, bem como apresentou maior energia cinética em 92% dos meses entre 1979 e 2010. O CFSR e o ERAI superestimaram os dados do ASCAT em 8% e 2%, respectivamente, mas se ajustaram satisfatoriamente bem, com baixos RMSE e altos coeficientes de correlação. Sugere-se que a maior energia existente no CFSR esteja associada a sua maior resolução espacial, o que possibilitaria maior amostragem dos fenômenos atmosféricos, e que o melhor ajuste do ERAI seja consequência de seu método de assimilação de dados mais robusto, o que compensaria a menor disponibilidade de dados in situ e remotos no Atlântico Sul. AbstractDue to the relevance of understanding atmospheric fluxes influence on the ocean state, especially the modeling and prediction of the interactions between these two systems, the present study aimed to climatologically compare two atmospheric reanalysis with respect to the energy of the sea surface winds to the Brazilian east/southeast continental shelf. The selected products were the Climate Forecast System Reanalysis (CFSR) and the ERA-Interim (ERAI), compared between 1979 and 2010 and validated according to Advanced Scatterometer (ASCAT) data between May/2007 and December/2010. Results demonstrated a clearly more energetic pattern of CFSR in relation to ERAI, either spatially and temporally, except for certain coastal areas. Quantitatively, the first product was 13% more intense on average and presented higher kinetic energy in 92% months between 1979 and 2010. The CFSR and the ERAI overestimated the ASCAT data by 8% and 2%, respectively, but satisfactorily adjusted, with low RMSE and high correlation coefficients. Then is suggested that the greater energy available in the CFSR was associated with its higher spatial resolution, which would allow a greater atmospheric phenomena sampling, and the best fit of the ERAI was a consequence of its more robust data assimilation method, which would compensate the less availability of in situ and remote data in South Atlantic.