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Validation of General Climate Models (GCMs) over Upper Blue Nile River Basin, Ethiopia

机译：埃塞俄比亚蓝尼罗河上游流域的一般气候模式（GCM）的验证

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摘要

Potential of climate change impact assessment on hydrology and water resources of rivers is increasing from time to time due to its importance for water resources planning and management in the future. In order to carry out climate change impact studies, using General Climate Models (GCM) is a common practice and before using any of these models, it is essential to validate the models for the selected study area. Blue Nile River is one of the most sensitive rivers towards climate change impacts. The main source of Blue Nile River is Lake Tana where the two adjacent tributary rivers, Ribb & Gumera, are located and the main object of this paper is validation of current 15 GCM outputs (IPCC-AR5) over these two rivers using empirical quantile perturbation downscaling technique. The performance of the downscaled outputs of GCMs were evaluated using statistical indicators and graphical techniques for evapotranspiration, rainfall and temperature variables using observed daily meteorological datasets collected from five stations (Addis Zemen, Bahirdar, Debretabor, Woreta and Yifag) for the control period 1971-2000. Analysis results showed that the correlation coefficient of all models for mean monthly (MM) rainfall are 12% - 45%; and the Bias and RMSE -46 mm to +169 mm and 62 mm to 241 mm, respectively. The Bias and RMSE for MM maximum temperature are -2.5°C to +35°C; and 1°C to 35°C whereas for MM minimum temperature -6°C to +22°C and 1.7°C to 23°C, respectively. For the case of MM evapotranspiration, which is estimated using FAO-Penman-Montheith equation, the Bias and RMSE values vary from -35 mm to +10 mm; and +11 mm to +36 mm, respectively. The variation in the performance level of these models indicates that there is high uncertainty in the GCM outputs. Therefore, to use these GCM models for any climate change studies in the basin, careful selection has to be made.
机译：气候变化对河流水文和水资源影响评估的潜力不时增加，因为它对未来水资源规划和管理的重要性。为了进行气候变化影响研究，使用通用气候模型（GCM）是一种常见做法，在使用任何这些模型之前，必须对所选研究区域的模型进行验证。青尼罗河是对气候变化影响最敏感的河流之一。蓝色尼罗河的主要来源是塔那湖，两个相邻的支流河Ribb和Gumera都位于此，本文的主要目的是使用经验分位数扰动来验证这两条河上当前的15 GCM输出（IPCC-AR5）缩小技术。使用统计指标和图形技术评估了GCM的缩减输出的性能，这些数据用于蒸发量，降雨量和温度变量，使用了五个时段（亚的斯亚西泽门，巴希尔达尔，德布列塔博尔，沃雷塔和伊法格）收集的日常气象数据，用于控制期1971- 2000。分析结果表明，所有模型与月平均降水量的相关系数为12％-45％。偏置和RMSE分别为-46毫米至+169毫米和62毫米至241毫米。 MM最高温度的偏置和RMSE为-2.5°C至+ 35°C;和1°C至35°C，而对于MM最低温度分别为-6°C至+ 22°C和1.7°C至23°C。对于MM蒸散量（使用FAO-Penman-Montheith方程估算），Bias和RMSE值从-35 mm到+10 mm不等;和+11毫米至+36毫米。这些模型的性能水平变化表明，GCM输出存在高度不确定性。因此，要将这些GCM模型用于流域内的任何气候变化研究，都必须谨慎选择。

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