Projections of changes in extreme climate are sometimes predicted by multimodel ensemble methods that combine forecasts from individual simulation models using weighted averaging. One method to assign weight to each model is the Bayesian model averaging (BMA) in which posterior probability is used. For the cases of extreme climate, the generalized extreme value distribution (GEVD) is typically used. We applied the approach of GEV‐embedded BMA to a series of 35 years of the annual maximum daily precipitation data (both historical data and data gathered from simulation experiments for future periods) over the Korean peninsula as simulated by the models in the Coupled Model Intercomparison Project Phase 5 (CMIP5). Simulation data under two Representative Concentration Pathway (RCP) scenarios, namely RCP4.5 and RCP8.5, were used. Observed data and 17 CMIP5 models for 12 gird cells in Korea have been examined to predict future changes in precipitation extremes. A simple regional frequency analysis of pooling observations from three stations in each cell was employed to reduce the estimation variance and local fluctuations. A bias correction technique using the regression‐type transfer function was applied to these simulation data. Return levels spanning over 20 and 50 years, as well as the return periods relative to the reference years (1971–2005), were estimated for two future periods, namely Period 1 (2021–2050) and Period 2 (2066–2095). From these analyses, relative increase observed in the spatially averaged 20‐year (50‐year) return level was approximately 23% (16%) and 45% (36%) in the RCP4.5 and RCP8.5 experiments, respectively, by the end of the 21st century. We concluded that extreme rainfalls will likely occur two times and four times more frequently in the RCP4.5 and RCP8.5 scenarios, respectively, as compared to in the reference years by the end of the 21st century.

中文翻译：

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CMIP5集合对朝鲜半岛极端降水的未来预测和不确定性评估

有时会通过多模型集成方法来预测极端气候变化的预测，这些方法会使用加权平均来组合来自各个模拟模型的预测。给每个模型分配权重的一种方法是使用后验概率的贝叶斯模型平均（BMA）。对于极端气候，通常使用广义极值分布（GEVD）。我们通过耦合模型比对中的模型对朝鲜半岛上连续35年的年度最大日降水量数据（包括历史数据和未来时期的模拟实验收集的数据）应用了GEV嵌入的BMA方法。项目第5阶段（CMIP5）。使用了两种代表性浓度途径（RCP）情况下的仿真数据，即RCP4.5和RCP8.5。已经检查了韩国12个网格细胞的观测数据和17个CMIP5模型，以预测未来极端降水的变化。通过对每个像元中三个站的合并观测值进行简单的区域频率分析，以减少估计方差和局部波动。使用回归类型传递函数的偏差校正技术已应用于这些模拟数据。估计了两个未来时期，即20年和50年的回报水平，以及相对于参考年（1971-2005年）的回报期，分别是1期（2021-2050）和2期（2066-2095）。根据这些分析，在RCP4.5和RCP8.5实验中，空间平均20年（50年）回报水平的相对增加分别约为23％（16％）和45％（36％）。 21世纪末。