Effect of warming climate on extreme daily rainfall depth using non-stationary Gumbel model with temperature co-variate

Abstract

In this study, non-stationary frequency analysis was carried out to apply non-stationarity of extreme rainfall driven by climate change using the scale parameter of two parameters of the Gumbel distribution (GUM) as a co-variate function. The surface air temperature (SAT) or dew-point temperature (DPT) is applied as the co-variate. The optimal model was selected by comparing AICs, and 17 of 60 sites were found to be suitable for the non-stationary GUM model. In addition, SAT was chosen as the more appropriate co-variate among 13 of the 17 sites. As a result of estimating changes in design rainfall depth with future SAT rises at 13 sites, it is likely to increase by 10% in 2040 and 18% in 2070. HIGHLIGHTS Rainfall extremes in Korea have non-stationary characteristics with co-variate of surface air temperature or dew-point temperature.; Non-stationary frequency analysis using SAT or DPT can be a reasonable approach for analyzing future rainfall extremes.;

Keywords

• climate change
• gumbel
• non-stationary frequency analysis