Renewable energy sources are increasing globally, mainly due to efforts to achieve net zero emissions. In Brazil, solar photovoltaic electricity generation has grown substantially in recent years, with the installed capacity rising from 2455 MW in 2018 to 47,033 MW in August 2024. However, the intermittency of solar energy increases the challenges of forecasting solar generation, making it more difficult for decision-makers to plan flexible and efficient distribution systems. In addition, to forecast power generation to support grid expansion, it is essential to have adequate data sources, but measured climate data in Brazil is limited and does not cover the entire country. To address this problem, this study evaluates the global horizontal irradiance (GHI) of four global reanalysis datasets—MERRA-2, ERA5, ERA5-Land, and CFSv2—at 35 locations across Brazil. The GHI time series from reanalysis was compared with ground-based measurements to assess its ability to represent hourly GHI in Brazil. Results indicate that MERRA-2 performed best in 90% of the locations studied, considering the root mean squared error. These findings will help advance solar forecasting by offering an alternative in regions with limited observational time series measurements through the use of reanalysis datasets.

Objectives No consensus exists about the best COVID-19 vaccination strategy to be adopted by low-income and middle-income countries. Brazil adopted an age-based calendar strategy to reduce mortality and the burden on the healthcare system. This study evaluates the impact of the vaccination campaign in Brazil on the progression of the reported COVID-19 deaths. Methods This ecological study analyses the dynamic of vaccination coverage and COVID-19 deaths in hospitalised adults (≥20 years) during the first year of the COVID-19 vaccination roll-out (January to December 2021) using nationwide data (DATASUS). We stratified the adult population into 20–49, 50–59, 60–69 and 70+ years. The dynamic effect of the vaccination campaign on mortality rates was estimated by applying a negative binomial regression. The prevented and possible preventable deaths (observed deaths higher than expected) and potential years of life lost (PYLL) for each age group were obtained in a counterfactual analysis. Results During the first year of COVID-19 vaccination, 266 153 517 doses were administered, achieving 91% first-dose coverage. A total of 380 594 deaths were reported, 154 091 (40%) in 70+ years and 136 804 (36%) from 50-59 or 20-49 years. The mortality rates of 70+ decreased by 52% (rate ratio [95% CI]: 0.48 [0.43-0.53]) in 6 months, whereas rates for 20–49 were still increasing due to low coverage (52%). The vaccination roll-out strategy prevented 59 618 deaths, 53 088 (89%) from those aged 70+ years. However, the strategy did not prevent 54 797 deaths, 85% from those under 60 years, being 26 344 (45%) only in 20–49, corresponding to 1 589 271 PYLL, being 1 080 104 PYLL (68%) from those aged 20–49 years. Conclusion The adopted aged-based calendar vaccination strategy initially reduced mortality in the oldest but did not prevent the deaths of the youngest as effectively as compared with the older age group. Countries with a high burden, limited vaccine supply and young populations should consider other factors beyond the age to prioritise who should be vaccinated first.

Una parte fundamental del proceso de previsión probabilística de energía eólica es tener en cuenta las previsiones de la velocidad del viento. Para obtener pronósticos probabilísticos precisos de la producción eólica ha sido desarrollada una metodología híbrida utilizando técnicas no paramétricas conocidas como SSA (Análisis Singular Espectral) y Estimación Condicional de la Densidad por Kernel (CKDE). SSA es empleada para predecir la velocidad del viento y CKDE para obtener previsiones probabilísticas de la energía eólica, dado que la generación de la energía eólica tiene una relación no lineal con la velocidad del viento y ambas son variables aleatorias distribuidas que siguen una función de densidad conjunta. Haciendo uso de una base de datos brasilera horaria que incluye la velocidad del viento y la energía eólica es ilustrada dicha metodología. Una vez que las previsiones de la velocidad del viento son obtenidas, los correspondientes pronósticos probabilísticos de la generación de energía eólica son estimados para un horizonte de 24 horas. Los resultados obtenidos son comparados con otras metodologías existentes.