Reanalysis Data Validation as a Tool to Support Agrometeorological Studies and SDG Monitoring in the Amazon: A Case Study of the 2023–2024 El Niño Event

Reliable climate information is essential for assessing extreme events and supporting environmental management in the Amazon, where sparse meteorological networks constrain climate monitoring. This study evaluated ERA5 and CFSR reanalysis datasets for estimating mean air temperature in Boa Vista, Belém, and Manaus during the 2023–2024 El Niño event. Reanalysis estimates were compared with Brazilian National Institute of Meteorology (INMET) observations using R2, MAE, RMSE, MBE, Taylor diagrams, and ANOVA followed by Tukey’s HSD test. ERA5 consistently outperformed CFSR, with higher R2 values (Boa Vista: 0.702 vs. 0.396; Belém: 0.606 vs. 0.336; Manaus: 0.787 vs. 0.339) and lower RMSE (1.06 vs. 2.40 °C; 0.59 vs. 1.40 °C; 0.94 vs. 2.15 °C, respectively). Substantial temperature differences were observed among the historical period (1990–2022), 2023, and 2024 (p < 0.001). These results demonstrate ERA5’s superior ability to represent air temperature variability during the 2023–2024 El Niño in the Brazilian Amazon. Validated ERA5 data can strengthen climate monitoring and support agricultural planning, drought assessment, climate adaptation, and environmental management, contributing to evidence-based actions related to SDGs 2, 11, 13, and 15.

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Journal
Sustainability
Published
2026-09-24
DOI
https://doi.org/10.3390/su18199776
Primary Topic
Climate variability and models
Type
article
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article

Reanalysis Data Validation as a Tool to Support Agrometeorological Studies and SDG Monitoring in the Amazon: A Case Study of the 2023–2024 El Niño Event

Alex Santos da Silva, Gabriel Brito Costa, H. N. Lima, Jorge L. Mazza Rodrigues et al.
Sustainability
Climate variability and models
article

Reanalysis Data Validation as a Tool to Support Agrometeorological Studies and SDG Monitoring in the Amazon: A Case Study of the 2023–2024 El Niño Event

Alex Santos da Silva, Gabriel Brito Costa, H. N. Lima, Jorge L. Mazza Rodrigues, Lucieta Guerreiro Martorano, Claudia Brandão, Theomar Neves, Ronie Silva Juvanhol, Marcos César da Rocha Seruffo, Roseilson Souza do Vale, Aurilene Barros dos Santos de Andrade, Elaine dos Santos, Leticia Matias, José Mora, Victor Uchoa, Petia Arruda, Nayara Mesquita, Camily Rabelo, Roberto Siqueira, Larice Marinho, Pio Lima, Renanzeller Rodrigues
article en

Abstract

Reliable climate information is essential for assessing extreme events and supporting environmental management in the Amazon, where sparse meteorological networks constrain climate monitoring. This study evaluated ERA5 and CFSR reanalysis datasets for estimating mean air temperature in Boa Vista, Belém, and Manaus during the 2023–2024 El Niño event. Reanalysis estimates were compared with Brazilian National Institute of Meteorology (INMET) observations using R2, MAE, RMSE, MBE, Taylor diagrams, and ANOVA followed by Tukey’s HSD test. ERA5 consistently outperformed CFSR, with higher R2 values (Boa Vista: 0.702 vs. 0.396; Belém: 0.606 vs. 0.336; Manaus: 0.787 vs. 0.339) and lower RMSE (1.06 vs. 2.40 °C; 0.59 vs. 1.40 °C; 0.94 vs. 2.15 °C, respectively). Substantial temperature differences were observed among the historical period (1990–2022), 2023, and 2024 (p < 0.001). These results demonstrate ERA5’s superior ability to represent air temperature variability during the 2023–2024 El Niño in the Brazilian Amazon. Validated ERA5 data can strengthen climate monitoring and support agricultural planning, drought assessment, climate adaptation, and environmental management, contributing to evidence-based actions related to SDGs 2, 11, 13, and 15.

SustainabilityVol. 18(19)
Brazilian Institute of Environment and Renewable Natural Resources (BR), Universidade Federal do Oeste do Pará (BR), Universidade Federal do Rio Grande do Norte (BR), University of California, Davis (US)
Climate action
Openalex Percentile: Top 14%
Climate variability and models
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