This paper has two primary purposes. First, we fit the annual maximum daily rainfall data for 6 rainfall stations, both with stationary and non-stationary generalized extreme value (GEV) distributions for the periods 1911-2010 and 1960-2010 in Taiwan, and detect the changes between the two phases for extreme rainfall. The non-stationary model means that the location parameter in the GEV distribution is a linear function of time to detect temporal trends in maximum rainfall. Second, we compute the future behavior of stationary models for the return levels of 10, 20, 50 and 100-years based on the period 1960-2010. In addition, the 95% confidence intervals of the return levels are provided. This is the first investigation to use generalized extreme value distributions to model extreme rainfall in Taiwan.

Q51, Q54, Q57, extreme rainfall, generalized extreme value, return level, statistical modelling
Erasmus School of Economics
Econometric Institute Research Papers
Report / Econometric Institute, Erasmus University Rotterdam
Erasmus School of Economics

Chu, L-F, McAleer, M.J, & Wang, S-H. (2012). Statistical Modelling of Recent Changes in Extreme Rainfall in Taiwan (No. EI 2012-36). Report / Econometric Institute, Erasmus University Rotterdam (pp. 1–12). Erasmus School of Economics. Retrieved from