Reduction of uncertainty in climate change projections is a major challenge in impact assessment and adaptation planning. General circulation models (GCMs) along with projection scenarios are the major sources of uncertainty in climate change projections. Therefore, the selection of appropriate GCMs for a region can significantly reduce uncertainty in climate projections. In this study, 20 GCMs were statistically evaluated in replicating the spatial pattern of monsoon propagation towards Peninsular Malaysia at annual and seasonal time frames against the 20th Century Reanalysis dataset. The performance evaluation metrics of the GCMs for different time frames were compromised using a state-of-art multi-criteria decision-making approach, compromise programming, for the selection of GCMs. Finally, the selected GCMs were interpolated to 0.25 × 0.25 spatial resolution and biascorrected using the Asian Precipitation – Highly-Resolved Observational Integration Towards Evaluation (APHRODITE) rainfall as reference data. The results revealed the better performance of BCC-CSM1-1 and HadGEM2-ES in replicating the historical rainfall in Peninsular Malaysia. The biascorrected projections of selected GCMs revealed a large variation of the mean, standard deviation and 95% percentile of daily rainfall in the study area for two futures, 2020–2059 and 2060–2099 compared to base climate. This is an Open Access article distributed under the terms of the Creative Commons Attribution Licence (CC BY 4.0), which permits copying, adaptation and redistribution, provided the original work is properly cited (http://creativecommons.org/licenses/by/4.0/). doi: 10.2166/nh.2020.154 ://iwaponline.com/hr/article-pdf/51/4/781/730910/nh0510781.pdf Saleem A. Salman Mohamed Salem Nashwan Tarmizi Ismail (corresponding author) Shamsuddin Shahid School of Civil Engineering, Faculty of Engineering, Universiti Teknologi Malaysia, 81310 Johor Bahru, Malaysia E-mail: tarmiziismail@utm.my Mohamed Salem Nashwan Department of Construction and Building Engineering, College of Engineering and Technology, Arab Academy for Science, Technology and Maritime Transport (AASTMT), 2033 Elhorria, Heliopolis, Cairo, Egypt

中文翻译：

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CMIP5大环流模式马来西亚半岛降水量输出的选择

减少气候变化预测的不确定性是影响评估和适应规划的主要挑战。大气环流模型 (GCM) 以及预测情景是气候变化预测中不确定性的主要来源。因此，为一个地区选择合适的 GCM 可以显着降低气候预测的不确定性。在这项研究中，对 20 个 GCM 进行了统计评估，以根据 20 世纪再分析数据集在年度和季节性时间范围内复制向马来西亚半岛传播的季风空间模式。使用最先进的多标准决策方法、折衷编程来选择 GCM，对不同时间范围内 GCM 的性能评估指标进行了妥协。最后，选定的 GCM 被插值到 0.25 × 0。25 空间分辨率和偏差使用亚洲降水 - 高分辨率观测整合评估 (APHRODITE) 降雨作为参考数据进行校正。结果显示 BCC-CSM1-1 和 HadGEM2-ES 在复制马来西亚半岛的历史降雨量方面表现更好。所选 GCM 的偏差校正预测显示，与基准气候相比，研究区 2020-2059 和 2060-2099 两个未来的平均日降雨量的平均值、标准差和 95% 的百分位变化很大。这是一篇根据知识共享署名许可 (CC BY 4.0) 条款分发的开放获取文章，该许可允许复制、改编和重新分发，前提是正确引用原始作品 (http://creativecommons.org/licenses/by/ 4.0/)。doi：10.2166/nh.2020.154：//iwaponline。