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Prediction of variability of precipitation in the Yangtze River Basin under the climate change conditions based on automated statistical downscaling

机译:基于自动统计降尺度的气候变化条件下长江流域降水变化预测

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摘要

Many impact studies require climate change information at a finer resolution than that provided by general circulation models (GCMs). Therefore the outputs from GCMs have to be downscaled to obtain the finer resolution climate change scenarios. In this study, an automated statistical downscaling (ASD) regression-based approach is proposed for predicting the daily precipitation of 138 main meteorological stations in the Yangtze River basin for 2010-2099 by statistical downscaling of the outputs of general circulation model (HadCM3) under A2 and B2 scenarios. After that, the spatial-temporal changes of the amount and the extremes of predicted precipitation in the Yangtze River basin are investigated by Mann-Kendall trend test and spatial interpolation. The results showed that: (1) the amount and the change pattern of precipitation could be reasonably simulated by ASD; (2) the predicted annual precipitation will decrease in all sub- catchments during 2020s, while increase in all sub-catchments of the Yangtze River Basin during 2050s and during 2080s, respectively, under A2 scenario. However, they have mix-trend in each sub-catchment of Yangtze River basin during 2020s, but increase in all sub-catchments during 2050s and 2080s, except for Hanjiang River region during 2080s, as far as B2 scenario is concerned; and (3) the significant increasing trend of the precipitation intensity and maximum precipitation are mainly occurred in the northwest upper part and the middle part of the Yangtze River basin for the whole year and summer under both climate change scenarios and the middle of 2040-2060 can be regarded as the starting point for pattern change of precipitation maxima.
机译:许多影响研究需要比一般循环模型(GCM)提供更精细分辨率的气候变化信息。因此,必须缩小GCM的输出以获得更高分辨率的气候变化方案。在这项研究中,提出了一种基于自动统计降尺度(ASD)回归的方法,通过在以下条件下通过对总环流模型(HadCM3)的输出进行统计降尺度,来预测2010年至2099年长江流域138个主要气象站的日降水量。 A2和B2方案。然后,利用Mann-Kendall趋势检验和空间插值方法,研究了长江流域的降水量时空变化和极端降水。结果表明:(1)ASD可以合理模拟降水量和变化规律; (2)在A2情景下,预测的年降水量将在2020年代所有子流域减少,而在2050年代和2080年代长江流域的所有子流域都将增加。但是,就B2情景而言,它们在2020年代长江流域的每个子汇水区都有混合趋势,但在2050年代和2080年代,除2080年代的汉江地区外,所有子汇水面积都有增加。 (3)在气候变化情景和2040-2060年中期间,全年和夏季降水强度和最大降水量的显着增加趋势主要发生在长江流域的西北上部和中部。可以看作是降水最大值模式变化的起点。

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    State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, People's Republic of China;

    State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, People's Republic of China;

    State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, People's Republic of China;

    State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, People's Republic of China,HydroChina Huadong Engineering Corporation, Hangzhou 310014, People's Republic of China;

    Department of Geosciences, University of Oslo, P. O. Box 1047, Blindern, 0316 Oslo, Norway,Department of Earth Sciences, Uppsala University, Uppsala, Sweden;

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  • 正文语种 eng
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  • 关键词

    climate change; statistical downscaling; mann-kendall trend; precipitation; the yangtze river basin;

    机译:气候变化;统计缩减;曼-肯德尔趋势沉淀;长江流域;

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