Sunshine Duration in Brazil From Meteosat (1983–2020): Climatology, Variability and Long‐Term Trends

ABSTRACT Sunshine duration (SDU) is a fundamental climatological variable with broad applications in agriculture, energy, health and tourism. However, despite its importance, Brazil lacks comprehensive country‐scale assessments, mainly due to deficiencies in the irregular and sparse in situ observation network. To overcome these limitations, this study employed the high‐resolution satellite‐based CMSAF SARAH‐3.0 SDU dataset for the 1983–2020 period, enabling a spatially consistent evaluation across Brazil. The analysis combined regional and gridded climatologies, Empirical Orthogonal Function (EOF) decomposition and robust trend assessment. Climatological results reveal strong regional contrasts: the Northeast records the highest and most regular SDU, while the South exhibits the lowest values. The largest (smallest) seasonal amplitude occurs in the North (Southeast). Also, the Central‐West exhibits a marked monsoonal cycle. EOF analysis identifies three leading modes of variability, associated with the South American Monsoon System, the Atlantic Intertropical Convergence Zone and a regional mode linked to intraseasonal variability over southeastern Brazil, the La Plata Basin and the adjacent South Atlantic. Long‐term analyses indicate generalised increases in SDU, with statistically significant positive trends in the Central‐West and Northeast, while the North and South display weaker and spatially heterogeneous tendencies. These findings fill a critical gap in Brazil's SDU climatology and underscore the need for continued monitoring to better understand the mechanisms driving observed changes and their implications for climate‐sensitive sectors.

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Journal
International Journal of Climatology
Published
2026-03-02
DOI
https://doi.org/10.1002/joc.70328
Primary Topic
Climate variability and models
Type
article
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article

Sunshine Duration in Brazil From Meteosat (1983–2020): Climatology, Variability and Long‐Term Trends

Maria Lívia Lins Mattos Gava, Íris Paraguay Silva,  Simone Marilene Sievert da Costa
International Journal of Climatology
Climate variability and models
article

Sunshine Duration in Brazil From Meteosat (1983–2020): Climatology, Variability and Long‐Term Trends

Maria Lívia Lins Mattos Gava, Íris Paraguay Silva,  Simone Marilene Sievert da Costa
article en

Abstract

ABSTRACT Sunshine duration (SDU) is a fundamental climatological variable with broad applications in agriculture, energy, health and tourism. However, despite its importance, Brazil lacks comprehensive country‐scale assessments, mainly due to deficiencies in the irregular and sparse in situ observation network. To overcome these limitations, this study employed the high‐resolution satellite‐based CMSAF SARAH‐3.0 SDU dataset for the 1983–2020 period, enabling a spatially consistent evaluation across Brazil. The analysis combined regional and gridded climatologies, Empirical Orthogonal Function (EOF) decomposition and robust trend assessment. Climatological results reveal strong regional contrasts: the Northeast records the highest and most regular SDU, while the South exhibits the lowest values. The largest (smallest) seasonal amplitude occurs in the North (Southeast). Also, the Central‐West exhibits a marked monsoonal cycle. EOF analysis identifies three leading modes of variability, associated with the South American Monsoon System, the Atlantic Intertropical Convergence Zone and a regional mode linked to intraseasonal variability over southeastern Brazil, the La Plata Basin and the adjacent South Atlantic. Long‐term analyses indicate generalised increases in SDU, with statistically significant positive trends in the Central‐West and Northeast, while the North and South display weaker and spatially heterogeneous tendencies. These findings fill a critical gap in Brazil's SDU climatology and underscore the need for continued monitoring to better understand the mechanisms driving observed changes and their implications for climate‐sensitive sectors.

International Journal of Climatology
Escola da Cidade (BR), Instituto Nacional de Pesquisas Espaciais (BR)
Openalex Percentile: Top 43%
Climate variability and models
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