摘要
降低不确定性影响是进行极值降水事件时空变异合理分析的前提。基于6种大气环流模式的输出结果,采用分位数映射校正方法和多模式集合平均方法降低不确定性影响,分析了长江流域极值降水指标的时空变异规律。结果表明:原始的气候模式输出结果具有较大的不确定性,必须对其进行定量分析和采取适当有效的措施进行缓解。5个极值降水指标总体上相对于基准期均增加,最大增幅10%左右。仅个别区域的极值降水指标显示出变异的时间一致性,而空间变异在相同情景和时段上差别明显。
Reducing uncertainty is the premise to obtain reasonable analysis of spatial and temporal variation for extreme precipita - tion events. Based on the methods of quantile mapping and multi-model ensemble, the uncertainty could be diminished and the output data of six general circulation models were downscaled to analyze the spatial and temporal variation of the Extreme Precipi-tation Indices (EPI) in the Yangtze River Basin. The results indicate that sufficient uncertainty exists in the original global circula - tion model output, so uncertainty analysis and eliminating its impact by useful measures is necessary. Each EPI tends to increase compared to the baseline period and the maximum increase may reach to about 10%. The EPI shows the consistency of variation only in several regions at temporal scale, while exhibits great difference at spatial scale for the same emission scenario and period.
出处
《水文》
CSCD
北大核心
2017年第3期14-21,共8页
Journal of China Hydrology
基金
国家自然科学基金项目(41401018
51409152
51509141)
梯级水电站运行与控制湖北省重点实验室开放基金(2015KJX02)
三峡大学人才科研启动基金(KJ2014B030)
关键词
长江流域
极值降水指标
不确定性
偏差校正
多模式集合
Yangtze River Basin
extreme precipitation indices
uncertainty
bias correction
multi-GCM ensemble