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Cluster analysis of rainfall patterns in Mamminasata: Validation of climate hazards group infrared precipitation with station dataset using observational comparisons

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dc.contributor.author Pasari, Sumanta
dc.date.accessioned 2025-02-14T10:18:15Z
dc.date.available 2025-02-14T10:18:15Z
dc.date.issued 2024
dc.identifier.uri https://ideas.repec.org/a/ajp/edwast/v8y2024i6p9555-9567id4035.html
dc.identifier.uri http://dspace.bits-pilani.ac.in:8080/jspui/handle/123456789/17727
dc.description.abstract This study aims to apply the cluster method to objectively classify rainfall patterns in the Mamminasata monsoon region based on observational data and Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) data. Validation was carried out using dichotomous and numerical comparisons with in situ observational data to strengthen the validity of CHIRPS data. The results showed that observational and CHIRPS data showed three different rainfall patterns. The first pattern shows rainfall at the beginning or end of the year ranging from 80-110 mm, decreasing after the 9th day of March, then increasing again in May to mid-June. The second pattern has a slightly lower rainfall intensity than the first one. The third pattern shows rainfall that increases beyond 100 mm at the end of each year, decreasing after February and reaching its lowest point in August. Towards the end of the year, there is an increase exponentially. CHIRPS rainfall predictions tend to overestimate in the southwest coastal area of Mamminasata, while underestimations are observed in the northern urban areas and eastern mountains. The accuracy of satellite rainfall estimates varies significantly across the Mamminasata region. In general, the performance of CHIRPS rainfall estimates is better in lowland areas than in mountainous areas. en_US
dc.language.iso en en_US
dc.subject Mathematics en_US
dc.subject CHIRPS data en_US
dc.subject Climate hazards group en_US
dc.title Cluster analysis of rainfall patterns in Mamminasata: Validation of climate hazards group infrared precipitation with station dataset using observational comparisons en_US
dc.type Preprint en_US


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