The Sun's Influence on Extreme Weather: A Study of Solar Declination and Sunlight Intensity on Rainfall Extremes in West Sumatra, July–December 2025

Abstract

West Sumatra is one of the regions in Indonesia that is vulnerable to extreme rains that often trigger hydrometeorological disasters, such as floods and flash floods. These incidents have an impact on infrastructure damage, disruption of socio-economic activities, and increased risks to public safety. This study aims to analyze the relationship between solar declination, light intensity, and extreme rainfall events in West Sumatra during July–December 2025. The study used 184 daily data points. Rainfall data were obtained from the West Sumatra Climatology Station, Teluk Bayur Maritime Meteorological Station, and Minangkabau Padang Pariaman Class II Meteorological Station. Light intensity data were obtained from the Class II Minangkabau Padang Pariaman Meteorological Station, while solar declination data were sourced from the National Oceanic and Atmospheric Administration (NOAA). The analysis was carried out using descriptive statistics, graphical visualization, spatial mapping with Surfer software, and Spearman correlation tests. The results show that the flash flood in East Malalak (Agam) on November 26, 2025 occurred when the Sun declinated around −21.3°, the intensity of light ranged from (160,000–180,000)W/m², and rainfall reached (200–220)mm. On 27–28 November 2025, light intensity decreased to (40,000–50,000)W/m², while rainfall increased to (430–500)mm and flooding extended to some areas in Agam, Padang, and Padang Panjang. The results of the Spearman test show that light intensity has a stronger negative relationship with precipitation compared to the declination of the Sun (ρ = −0.428), so it has the potential to be a supporting parameter in monitoring atmospheric conditions when combined with other meteorological parameters. This study is limited to the use of light intensity data from a single observation station and correlation analysis that only shows statistical relationships, so further research with multi-station data and more diverse atmospheric variables is needed to gain a more comprehensive understanding.