利用埃塞俄比亚卡塔尔流域的观测气候模型和区域气候模型对变量气候模型进行性能评估

Babur Tesfaye Yersaw, Mulusew Bezabih Chane, Natnael Andualem Yitayew
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引用次数: 0

摘要

气候模型是估算可靠的未来气候变化及其对流域水资源和农业影响的基本工具。然而,并非所有气候模型都适用于所有地区。因此,为特定研究区域确定最合适的气候模型至关重要。本研究的重点是评估区域气候模式在模拟卡塔流域降水和温度方面的性能。本研究采用皮尔逊相关系数(R)、平均绝对误差(MAE)、均方根误差(RMSE)和偏差等统 计指标,对 1984-2005 年期间 14 个 CORDEX-AFRICA-220 区域气候模式(RCM)的性能进行了检验。研究结果表明,GERICS-MPI 在代表 Areta 和 Bokoji 站方面表现较好,GERICS-IPSL 在代表 Assela、Ketergenet 和 Sagure 站方面表现较好,CCCma-CanESM2-AFR22 和 RCA4-ICHEC 分别在代表 Kulumsa 和 Ogolcho 站的年平均观测降雨量方面表现相对较好。然而,RCA4-CSIRO 在估算所有站点的年降雨量方面表现较弱。在复制 Areta、Bokoji 和 Ketergenet 站的最高气温年度模式方面,GERICS-MPI 等 RCM 模型相对优于其他模型。同样,GERICS-IPSL 在复制 Assela 和 Sagure 站的年最高气温方面相对较好,Kulumsa 站的 CCCma-CanESM2-AFR22 和 Ogolcho 站的 RCA4-ICHEC 在捕捉观测和模拟的年最高气温方面表现良好。Areta 站、Assela 站和 Ketergenet 站的 CCCma-CanESM2-AFR22 和 Bokoji 站的 GERICS-MOHE-AFR-22、Kulumsa 站和 Ogolcho 站的 GERICS-MPI 以及 Sagure 站的 RAC4-NOAA-2G 在最低气温方面表现较好。不过,RCA4-CSIRO 在所有站点的表现都较弱。GERICS-MPI 和 CCLM4-NCC-AFR-22 的 RCM 模型在校正 Katar 流域年降雨量方面的表现优于其他 RCM 模型。但 RCA4-ICHEC 模型在卡塔流域的表现较差。GERICS-MPI 模型表现良好。然而,RCA4-ICHEC 模型在卡塔流域的最高气温方面表现不佳,GERICS-NOAA-2M 模型在卡塔流域的最低气温方面表现不佳。
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Performance evaluation of varies climate models using observed and regional climate models for the Katar Watershed, Ethiopia
Climate models are fundamental tools to estimates the reliable future climate change and its effects on the water resources and agriculture in basins. However, all climate models are not equally performed for all areas. Therefore, determining the most appropriate climate models for a specific study area is essential. The focus of this study was to evaluate the performance of the regional climate models with regard to simulating precipitation, and temperatures at Katar watershed. This study examines the performance of fourteen CORDEX-AFRICA-220 Regional Climate Models (RCMs) for the period of 1984–2005 using statistical metrics such as Pearson correlation coefficient (R), mean absolute error (MAE), root mean squared error (RMSE), and bias. The findings indicated that GERICS-MPI was better performed in representing Areta, and Bokoji station, GERICS-IPSL was better representing in Assela, Ketergenet, and Sagure station, CCCma-CanESM2-AFR22, and RCA4-ICHEC performed relatively better in representing the mean annual observed rainfall at the Kulumsa, and Ogolcho station respectively. However, RCA4-CSIRO performed weakly in estimation of annual rainfall at all stations. RCM model such as GERICS-MPI was relatively better than the others in replicating the annual pattern of the maximum temperature at Areta, Bokoji, and Ketergenet stations. Similarly, GERICS-IPSL were relatively better in replicating the annual maximum temperature at Assela, and Sagure stations, CCCma-CanESM2-AFR22 at Kulumsa station, and RCA4-ICHEC at Ogolcho station performed well in capturing the observed and simulated annual maximum temperature. Better performance was observed on minimum temperature at CCCma-CanESM2-AFR22 at Areta, Assela, and Ketergenet stations, GERICS-MOHE-AFR-22 at Bokoji station, GERICS-MPI at Kulumsa, and Ogolcho stations, RAC4-NOAA-2G at Sagure stations. However, weak performance was observed RCA4-CSIRO at all stations. RCM models of GERICS-MPI, and CCLM4-NCC-AFR-22 performed better than the other RCM models for correction of annual rainfall in Katar watershed. However, poor performance was observed at RCA4-ICHEC model on Katar watershed. The GERICS-MPI model performed well. However, poor performance was observed at RCA4-ICHEC on maximum temperature, and GERICS-NOAA-2M on minimum temperature in Katar watershed.
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