The São Francisco River basin is one of the largest in the Brazilian territory. This basin has enormous economic, social and cultural importance for the country. Its water is used for human and animal supply, irrigation and energy production. This basin is located in an area with different climatic characteristics (humid and semiarid) and studies related to precipitation are very important in this region. In this scenario, the objective of this investigation is to present an assessment of rainfall estimated through the Integrated Multi-SatellitE Retrievals for Global Precipitation Measurement (IMERG) product compared with rain gauges over the São Francisco river basin in Brazil. For that, a period from of 20 years and 18 surface weather stations were used to evaluate the product. Based on different evaluation techniques, the study found that the IMERG is appropriate to represent precipitation over the basin. According to the results, the performance of the IMERG product depends on the location where the rain occurs. The bias ranged from −1.67 to 0.34 mm, the RMSE ranged from 5.36 to 10.36 mm and the values of the correlation coefficients between the daily data from the IMERG and rain gauge ranged from 0.28 to 0.61. The results obtained by Student t-test, density curves and regression analysis, in general, show that the IMERG is able to satisfactorily represent rain gauge data. The exception is the eastern portion of the basin, where the product, on average, underestimates the precipitation (p-value < 0.05) and presents the worst statistical metrics.

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Although seasonally dry tropical forests are considered invaluable to a greater understanding of global carbon fluxes, they remain as one of the ecosystems with the fewest observations. In this context, ecological and ecosystem models can be used as alternative methods to answer questions related to the interactions between the biosphere and the atmosphere in dry forests. The objective of this study was to calibrate the simple tropical ecosystem model (SITE) and evaluate its performance in characterizing the annual and seasonal behavior of the energy and carbon fluxes in a preserved fragment of the Caatinga biome. The SITE model exhibited reasonable applicability to simulate variations in CO2 and energy fluxes (r > 0.7). Results showed that the calibrated set of vegetation parameters adequately simulated gross primary productivity (GPP) and net ecosystem CO2 exchange (NEE). The SITE model was also able to accurately retrieve the time at which daily GPP and NEE peaked. The model was able to simulate the partition of the available energy into sensible and latent heat fluxes and soil heat flux when the calibrated parameters were used. Therefore, changes in the dynamics of dry forests should be taken into consideration in the modeling of ecosystem carbon balances.

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This study evaluated the atmospheric pattern precursors to the occurrence of natural disasters (ND) in the southern region of Brazil (SRB) due to the passage of frontal systems (FS). The results can be used as prognostics to assist in risk management with a set of preventive and mitigating actions in order to minimize the impact of natural disasters suffered by the population. The natural disasters data were provided by the Centro de monitoramento e alertas de desastres naturais (Cemaden). For atmospheric analysis we used ERA5 reanalysis data, and the precipitation dataset was estimated from Integrated Multi-satellitE Retrievals for GPM (IMERG) from the Global Precipitation Measurement (GPM) mission. The most affected regions are the coast of Santa Catarina and the central-eastern region of Rio Grande do Sul. The results indicate that FS associated with ND are different from the other FS that affect the SRB. The observations were: a pattern of increase and accumulation of available convective potential energy west of the SRB before the event, especially in spring; a considerable increase in specific humidity at low levels associated with runoff east of the Andes; and an anticyclonic circulation at high levels similar to the Bolivian High. Analysis of rainfall behavior indicates that it is highest in the two days preceding the disaster. The mean precipitation values identified, together with atmospheric behavior observed in this study, allow us to identify the potential occurrence of a disaster in the cities of SRB in the passage of a frontal system.

In this study, we evaluated the performance of the Brazilian Global Atmospheric Model (BAM), in its version 2.2.1, in the representation of the surface variables solar radiation, temperature (maximum, minimum, and average), and wind speed. Three experiments were carried out for the period from 2016 to 2022 under three different aerosol conditions (constant (CTE), climatological (CLIM), and equal to zero (ZERO)), discarding the first year as a spin-up period. The observations came from a high-resolution gridded analysis that provides Brazil with robust data based on observations from surface stations on a daily scale from 1961 to 2020; therefore, combining the BAM outputs with the observations, our intercomparison period took place from 2017 to 2020, for three timescales: daily, 10-day average, and monthly, targeting different applications. In its different simulations, BAM overestimated solar radiation throughout Brazil, especially in the Amazon; underestimated temperature in most of the northeast, southeast, and south regions; and overestimated in parts of the north and mid-west; while wind speed was only not overestimated in the Amazon region. In relative terms, the simulations with constant aerosol showed better performance than the others, followed by climatological conditions and zero aerosol. The dexterity indices applied in the intercomparison between BAM and observations indicate that BAM needs adjustments and calibration to better represent these surface variables. Where model deficiencies have been identified, these can be used to drive model development and further improve the predictive capabilities.

O objetivo principal neste trabalho foi avaliar a estimativa da evapotranspiração pelo algoritmo SEBAL (surface energy balance algorithm for land) no semiárido brasileiro. Para isso foi feito um levantamento bibliográfico acerca do tema, para diagnosticar se há convergência sobre a eficiência da utilização do SEBAL na aplicação e planejamento dos recursos hídricos, fazendo-se análise comparativa de diversos estudos publicados no meio científico. Os principais resultados encontrados convergiram que o SEBAL é um bom método, pois o erro oscila suavemente comparado as estimativas convencionais, além de permitir larga escala geográfica, análise com alta resolução e baixo custo. Considera-se que o SEBAL, embora tenha limitações com interferências atmosféricas, pode ser utilizado, o que se recomenda é que admita a margem de erro e que se faça análises com séries históricas para validar estatisticamente os resultados.