Abstract
The annual daily maximum precipitation (rx1day) is widely used to represent extreme events and is an important parameter in climate change studies. However, the climate variability in rx1day is sensitive to outliers and has difficulty representing the characteristics of large areas. We propose to use the probability index (PI), based on the cumulative density function (CDF) of a generalized extreme value (GEV) distribution to fit and standardize the rx1day to represent extreme event records in this study. A good correlation between the area-averaged PIs of the observed stations and those of the gridded dataset can be found over Taiwan. From the past PI records, there is no distinct trend in western Taiwan before the end of the 20^(th) century, but a climate regime change happened during 2002 - 2003. The dual change effects from both the variance and linear trend of extreme events are identified over the northeastern and southern parts of Taiwan, along with the island's central and southern regions, showing different abrupt changing trends and intensity. The PI can also be calculated using climate projection data to represent the characteristics of future extreme changes. The climate variability of PIs on the present (ALL) and future (RCP4.5 and RCP8.5) scenarios were evaluated using the 16 Couple Model Intercomparison Projects Phase-5 models (CMIP5). The simulated present fluctuations in PIs are smaller than those of actual observations. In the 21^(st) century, the RCP8.5 scenario shows that the PI significantly increases by 10% during the first half of the century, and 14% by the end of the century.
Highlights
Taiwan features a complex topography characterized by mountainous regions and rugged terrain, where rivers are short, valleys are narrow and geological features are fragile
Previous studies have verified that the annual maximum precipitation is highly related to the contribution from typhoon rainfall (Chen and Lu 2007; Lu et al 2007)
It can be seen that the fluctuation of rx1day anomaly of Taipei is the smallest among 4 stations, but the probability index (PI) anomaly fluctuation of Taipei is comparable to others
Summary
Taiwan features a complex topography characterized by mountainous regions and rugged terrain, where rivers are short, valleys are narrow and geological features are fragile. The global rx1day of land-based observation stations have validated a 7.2% K-1 increase in the period 1960 - 2009 (Westra et al 2013), as well as a 6% K-1 in the late 20th century from 1986 - 2005 in Couple Model Intercomparison Projects Phase 5 (CMIP5) multimodel experiments (Kharin et al 2013) These studies represent global-scale information, but the data are considered too rough for downstream applications in Taiwan. We propose a method that can effectively validate the extreme rainfall variance and trend over Taiwan, and reduce the impact of outliers associated with complicated topography
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