Template-type: ReDIF-Paper 1.0
Author-Name: Lan-Fen Chu
Author-Workplace-Name: National Science and Technology Center for Disaster Taiwan 
Author-Name: Michael McAleer
Author-Person: pmc90 
Author-Workplace-Name: Econometric Institute, Erasmus School of Economics, Erasmus University Rotterdam.
Author-Name: Ching-Chung Chang
Author-Workplace-Name: Institute of Economics Academia Sinica, Taiwan
Title: Statistical Modelling of Extreme Rainfall in Taiwan
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.
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.
Length: 20 pages 
Creation-Date: 2012-12  
Number: 2012-27 
X-File-Ref: http://america.sim.ucm.es/repec/ucm/ref/doicae1227.txt
File-URL: https://eprints.ucm.es/id/eprint/17472/1/1227.pdf
File-Format: Application/pdf
Handle: RePEc:ucm:doicae:1227