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Global Horizontal Irradiance in Brazil: A Comparative Study of Reanalysis Datasets with Ground-Based Data

Author

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  • Margarete Afonso de Sousa Guilhon Araujo

    (Department of Industrial Engineering, Pontifical Catholic University of Rio de Janeiro (PUC-Rio), Rua Marquês de São Vicente, 225, Gávea, Rio de Janeiro 22453-900, RJ, Brazil)

  • Soraida Aguilar

    (Department of Industrial Engineering, Pontifical Catholic University of Rio de Janeiro (PUC-Rio), Rua Marquês de São Vicente, 225, Gávea, Rio de Janeiro 22453-900, RJ, Brazil)

  • Reinaldo Castro Souza

    (Department of Industrial Engineering, Pontifical Catholic University of Rio de Janeiro (PUC-Rio), Rua Marquês de São Vicente, 225, Gávea, Rio de Janeiro 22453-900, RJ, Brazil)

  • Fernando Luiz Cyrino Oliveira

    (Department of Industrial Engineering, Pontifical Catholic University of Rio de Janeiro (PUC-Rio), Rua Marquês de São Vicente, 225, Gávea, Rio de Janeiro 22453-900, RJ, Brazil)

Abstract

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.

Suggested Citation

  • Margarete Afonso de Sousa Guilhon Araujo & Soraida Aguilar & Reinaldo Castro Souza & Fernando Luiz Cyrino Oliveira, 2024. "Global Horizontal Irradiance in Brazil: A Comparative Study of Reanalysis Datasets with Ground-Based Data," Energies, MDPI, vol. 17(20), pages 1-25, October.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:20:p:5063-:d:1496819
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    References listed on IDEAS

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    1. Paolo Di Leo & Alessandro Ciocia & Gabriele Malgaroli & Filippo Spertino, 2025. "Advancements and Challenges in Photovoltaic Power Forecasting: A Comprehensive Review," Energies, MDPI, vol. 18(8), pages 1-28, April.

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