Abstract
One of the most common ways to investigate changes in future rainfall extremes is to use future rainfall data simulated by climate models with climate change scenarios. However, the projected future design rainfall intensity varies greatly depending on which climate model is applied. In this study, future rainfall Intensity–Duration–Frequency (IDF) curves are projected using various combinations of climate models. Future Ensemble Average (FEA) is calculated using a total of 16 design rainfall intensity ensembles, and uncertainty of FEA is quantified using the coefficient of variation of ensembles. The FEA and its uncertainty vary widely depending on how the climate model combination is constructed, and the uncertainty of the FEA depends heavily on the inclusion of specific climate model combinations at each site. In other words, we found that unconditionally using many ensemble members did not help to reduce the uncertainty of future IDF curves. Finally, a method for constructing ensemble members that reduces the uncertainty of future IDF curves is proposed, which will contribute to minimizing confusion among policy makers in developing climate change adaptation policies.
Highlights
Future extreme weather events due to climate change have been extensively studied since they have potential impacts on human society and ecosystems [1]
In the IPCC Fifth Assessment Report [2], the Representative Concentration Pathways (RCPs) were introduced to form climate change scenarios, and in all of the greenhouse gas emission scenarios described in the report, surface air temperature is expected to rise throughout the 21st century
South Korea is located in the mid-latitude region, and projection results have been reported in most mid-latitude regions that the intensity of rainfall extremes will intensify in the future [7]
Summary
Future extreme weather events due to climate change have been extensively studied since they have potential impacts on human society and ecosystems [1]. It is not easy to quantify uncertainties numerically because future IDF curves are affected by various factors such as duration, return period, and region as well as GCMs, RCMs, RCP scenarios, and bias correction techniques. Yoon and Cho [53] performed uncertainty analyzes of rainfall extremes through multiple model ensembles of 9 GCMs. Lee et al [54] estimated the design rainfall depth using a traditional bootstrap technique and evaluated the uncertainty of future design flood. The rate of change and uncertainty behavior for return period and duration were explored
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