Rainfall estimation using Himawari-9 satellite data: A case study of Nakhon Sawan Province
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Abstract
Every year, Nakhon Sawan Province is affected by water-related disasters, including floods and droughts. Therefore, high-accuracy rainfall data and comprehensive coverage are crucial for effective water management. The main objective of this study was to estimate daily rainfall using data from the Himawari-9 satellite based on cloud-top brightness temperature. The study analyzed the Pearson correlation (r) and developed a model for estimating daily rainfall. Additionally, three rainfall estimation methods were compared using Himawari-9 satellite data: 1) Auto-Estimator, 2) IMSRA, and 3) Non-Linear Relation (NLR). These methods were calibrated using rain gauge data from meteorological stations via linear regression, and their errors were evaluated in Microsoft Excel. The results showed that all three methods had moderate to high correlations between satellite-derived and observed rainfall, which were significant at the 0.01 level. Among them, the NLR method proved to be the most suitable for practical use, with the highest correlation (r = 0.7163) and the lowest Root Mean Square Error (RMSE) of ±7.61 mm/day and Mean Absolute Deviation (MAD) of 3.84 mm/day.
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References
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