Statistical Modelling of Recent Changes in Extreme Rainfall in Taiwan
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.
|, , , , , ,|
|Erasmus School of Economics|
|Econometric Institute Research Papers|
|Report / Econometric Institute, Erasmus University Rotterdam|
|Organisation||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 http://hdl.handle.net/1765/38692