Statistical Modelling of Extreme Rainfall in Taiwan

Lan-Fen Chu, Michael McAleer and Ching-Chung Chang
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Lan-Fen Chu: National Science and Technology Center for Disaster Taiwan
Ching-Chung Chang: Institute of Economics Academia Sinica, Taiwan

No 2012-27, Documentos de Trabajo del ICAE from Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico

Abstract: In this paper, the annual maximum daily rainfall data from 1961 to 2010 are modelled for 18 stations in Taiwan. We fit the rainfall data with stationary and non-stationary generalized extreme value distributions (GEV), and estimate their future behaviour based on the best fitting model. The non-stationary model means that the parameter of location of the GEV distribution is formulated as linear and quadratic functions of time to detect temporal trends in the maximum rainfall. Future behavior refers to the return level and the return period of the extreme rainfall. The 10, 20, 50 and 100-years return levels and their 95% confidence intervals of the return levels stationary models are provided. The return period is calculated based on the record-high (ranked 1st) extreme rainfall brought by the top 10 typhoons for each station in Taiwan. The estimates show that non-stationary model with increasing trend is suitable for the Kaohsiung, Hengchun, Taitung and Dawu stations. The Kaohsing and Hengchun stations have greater trends than the other two stations, showing that the positive trend extreme rainfall in the southern region is greater than in the eastern region of Taiwan. In addition, the Keelung, Anbu, Zhuzihu, Tamsui, Yilan, Taipei, Hsinchu, Taichung, Alishan, Yushan and Tainan stations are fitted well with the Gumbel distribution, while the Sun Moon Lake, Hualien and Chenggong stations are fitted well with the GEV distribution.

Keywords: Extreme theory; Extreme rainfall; Return level; Typhoon. (search for similar items in EconPapers)
Pages: 20 pages
Date: 2012-12
Note: For financial support, the first and third authors are grateful to the Taiwan Climate Change Projection and Information Platform Project (NSC 100-2621-M-492-001), and the second author wishes to acknowledge the Australian research Council, National science Council, Taiwan, and the Japan Society for the promotion of Science.
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https://eprints.ucm.es/id/eprint/17472/1/1227.pdf (application/pdf)

Related works:
Working Paper: Statistical Modelling of Extreme Rainfall in Taiwan (2013)
Working Paper: Statistical Modelling of Extreme Rainfall in Taiwan (2013)
Working Paper: Statistical Modelling of Extreme Rainfall in Taiwan (2012)
Working Paper: Statistical Modelling of Extreme Rainfall in Taiwan (2012)
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