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Wavelet analysis of possible association between sunspot number and rainfall over Kerala, India: A case study

Published 14 Nov 2024 in physics.space-ph, physics.ao-ph, physics.data-an, and stat.AP | (2411.09234v1)

Abstract: Global attention has been focused on extreme climatic changes. This paper investigates the relationship between different phases of solar activity and extreme precipitation events in Kerala, India. Sunspot number and rainfall data were analysed over 122 years (1901-2022) on an annual scale. A negative correlation was observed in the winter and post-monsoon seasons, while positive correlations were seen in the pre-monsoon and monsoon seasons, all of which were statistically significant. Using cross-wavelet transform, the temporal relationship between sunspot number and rainfall values was investigated, revealing significant cross-power at an 8-12 year scale across all seasons. Wavelet coherence between the two data sets demonstrated significant correlation at the 2-4 and 4-8 year scales throughout the four seasons. The results show that the seasonal rainfall over Kerala is related to solar activity. The solar phases of Solar Cycles 14-24 were determined for all seasons, and the years with excessive and insufficient rainfall were identified. It was observed that the descending phase had an impact on excess rainfall events during the winter and pre-monsoon seasons, while the ascending phase notably affected the monsoon and post-monsoon seasons. The study specifically examined the different magnetic polarities of sunspots in alternating solar cycles, focusing on even and odd cycles. It was found that extreme rainfall events were more frequent during the winter and pre-monsoon seasons in the even cycles, whereas in the odd cycles, they were more prevalent during the monsoon and post-monsoon seasons. These findings are presented for the first time and may offer new perspectives on how different phases affect rainfall. This study suggests a physical link between solar activity and extreme precipitation in Kerala, which could increase predictability.

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