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Evaluation of regional climate models performance in simulating rainfall climatology of Jemma sub-basin, Upper Blue Nile Basin, Ethiopia

机译:埃塞俄比亚上尼罗河上游盆地杰玛次流域模拟降雨气候的区域气候模型性能评估

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This study examines the performance of 10 Regional Climate Model (RCM) outputs which are dynamically downscaled from the fifth phase of Coupled Model Inter-comparison Project (CMIP5) GCMs using different RCMs parameterization approaches. The RCMs are evaluated based on their ability to reproduce the magnitude and pattern of monthly and annual rainfall, characteristics of rainfall events and variability related to Sea Surface Temperature (SST) for the period 1981-2005. The outputs of all RCMs showed wet bias, particularly in the higher elevation areas of the sub-basin. Wet bias of annual rainfall ranges from 9.60% in CCLM4 (HadGEM2-ES) model to 110.9% in RCA4 (EC-EARTH) model. JJAS (June-September) rainfall is also characterized by wet bias ranges from 0.76% in REMO (MPI-ESM-LR) model to 100.7% in RCA4 (HadGEM2-ES) model. GCMs that were dynamically downscaled through REMO (Max Planck Institute) and CCLM4 (Climate Limited-Area Modeling) performed better in capturing the rainfall climatology and distribution of rainfall events. However, GCMs dynamically downscaled using RCA4 (SMHI Rossby Center Regional Atmospheric Model) were characterized by overestimation and there are more extreme rainfall events in the cumulative distribution. Most of the RCMs' rainfall over the sub-basin showed a teleconnection with Sea Surface Temperature (SST) of CMIP5 GCMs in the Pacific and Indian Oceans, but weak. The ensemble mean of all 10 RCMs simulations was superior in capturing the seasonal pattern of the rainfall and had better correlation with observed annual (Correl = 0.6) and JJAS season rainfall (Correl = 0.5) than any single model (S-RCM). We recommend using GCMs downscaled using REMO and CCLM4 RCMs and stations based statistical bias correction to manage elevation based biases of RCMs in the Upper Blue Nile Basin, specifically in the Jemma sub-basin.
机译:这项研究研究了10种区域气候模型(RCM)输出的性能,这些输出是使用不同的RCM参数化方法从耦合模型比较项目(CMIP5)GCM的第五阶段动态缩减的。根据RCM再现1981年至2005年期间月度和年度降雨量的大小和模式,降雨事件的特征以及与海表温度(SST)相关的变化性的能力,对RCM进行评估。所有RCM的输出均显示出湿偏斜,特别是在该次流域的高海拔地区。年降雨量的湿偏差范围从CCLM4(HadGEM2-ES)模型中的9.60%到RCA4(EC-EARTH)模型中的110.9%。 JJAS(6月至9月)降雨的特征还在于湿偏斜,范围从REMO(MPI-ESM-LR)模型中的0.76%到RCA4(HadGEM2-ES)模型中的100.7%。通过REMO(马克斯·普朗克研究所)和CCLM4(气候有限区域建模)进行动态缩减的GCM在捕获降雨气候学和降雨事件的分布方面表现更好。但是,使用RCA4(SMHI Rossby中心区域大气模型)动态缩减的GCM具有过高估计的特征,并且累积分布中还有更多的极端降雨事件。该次流域的大多数RCM降雨显示与太平洋和印度洋CMIP5 GCM的海表温度(SST)遥相关,但微弱。与所有单个模型(S-RCM)相比,所有10个RCM模拟的集合均值均能更好地捕获降雨的季节性模式,并且与观测到的年降水量(Correl = 0.6)和JJAS季节降水量(Correl = 0.5)具有更好的相关性。我们建议使用通过REMO和CCLM4 RCM降级的GCM,以及基于站台的统计偏差校正,以管理Blue Blue Nile盆地,特别是Jemma子盆地中RCM的基于海拔的偏差。

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