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Open AccessArticle
Synthetic Rainfall Modeling Using a Modified Hybrid Gamma-GP Distribution
by
Hyang Gon Jin
Hyang Gon Jin 1,
Seunghyun Hong
Seunghyun Hong 1
and
Yongku Kim
Yongku Kim 1,2,*
1
Department of Statistics, Kyungpook National University, Daegu 41566, Republic of Korea
2
KNU G-LAMP Research Center, Institute of Basic Sciences, Kyungpook National University, Daegu 41566, Republic of Korea
*
Author to whom correspondence should be addressed.
Appl. Sci. 2025, 15(17), 9563; https://doi.org/10.3390/app15179563 (registering DOI)
Submission received: 27 July 2025
/
Revised: 29 August 2025
/
Accepted: 29 August 2025
/
Published: 30 August 2025
Abstract
Stochastic weather generators are commonly employed to create synthetic sequences of daily weather variables across diverse fields, including hydrological, ecological, and agricultural studies. Realistic precipitation sequences, in particular, serve as essential inputs in numerous modeling frameworks. Generalized linear models (GLMs) that incorporate covariates to capture seasonality and teleconnections represent one effective approach for stochastic weather generation. However, these models often underestimate the interannual variability of seasonally aggregated variables, notably precipitation intensity during wet seasons. Recent methods developed to mitigate the issue of overdispersion have nevertheless struggled to adequately replicate observed precipitation intensities in wet seasons. To overcome this limitation, we propose integrating a modified hybrid gamma and generalized Pareto distribution into the GLM-based weather generator. This enhanced method was evaluated using daily precipitation data from Seoul, Korea, and successfully reproduced realistic precipitation intensities while effectively addressing the overdispersion issue.
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MDPI and ACS Style
Jin, H.G.; Hong, S.; Kim, Y.
Synthetic Rainfall Modeling Using a Modified Hybrid Gamma-GP Distribution. Appl. Sci. 2025, 15, 9563.
https://doi.org/10.3390/app15179563
AMA Style
Jin HG, Hong S, Kim Y.
Synthetic Rainfall Modeling Using a Modified Hybrid Gamma-GP Distribution. Applied Sciences. 2025; 15(17):9563.
https://doi.org/10.3390/app15179563
Chicago/Turabian Style
Jin, Hyang Gon, Seunghyun Hong, and Yongku Kim.
2025. "Synthetic Rainfall Modeling Using a Modified Hybrid Gamma-GP Distribution" Applied Sciences 15, no. 17: 9563.
https://doi.org/10.3390/app15179563
APA Style
Jin, H. G., Hong, S., & Kim, Y.
(2025). Synthetic Rainfall Modeling Using a Modified Hybrid Gamma-GP Distribution. Applied Sciences, 15(17), 9563.
https://doi.org/10.3390/app15179563
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