| 降尺度CMIP6模式对新疆降水模拟评估 |
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| 引用本文： | 胡家晖,孙彩霞,董思言,王磊斌,欧阳鸿翔,吴志文,钟校尧.降尺度CMIP6模式对新疆降水模拟评估[J].新疆气象,2024,18(5). |
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| 作者姓名： | 胡家晖 孙彩霞 董思言 王磊斌 欧阳鸿翔 吴志文 钟校尧 |
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| 作者单位： | 新疆维吾尔自治区气候中心,新疆维吾尔自治区气候中心,国家气候中心 北京 河北师范大学 石家庄,,江西省气象台 南昌,中国能源建设集团广东省电力设计研究院有限公司 广州, |
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| 基金项目： | 新疆气象局科技创新发展青年(QN202307) |
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| 摘 要： | 基于6个CMIP6模式的日降水量数据，采用降尺度方法将其统一分辨率到0.25°×0.25°，选取5个极端降水指数从降水气候态、极端性、季节性三个角度对新疆区域1961—2014年历史期降水模拟效果评估。结果表明，降尺度CMIP6模式能较好再现新疆区域降水的空间分布特征，最大年均降水量误差小于30 mm，夏季降水模拟效果最佳相关系数均高于0.8。模式在春秋季对降水的模拟效果差异较小，标准差比值均在1.00 ~ 1.25之间，ACCESS-CM2模拟效果最佳。模式集合均值能模拟出观测降水增多趋势，但低估了降水的年际变率，模拟结果提示新疆80年代的降水转折可能与人类活动有关。在降水极端性和季节性方面，降尺度数据对新疆的极端降水和季节性降水均有较好的模拟性能，降尺度数据对季节性降水的模拟能力（与观测均值误差小于0.001）比原始分辨率的数据（与观测误差大于0.005）效果更好。
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| 关 键 词： | CMIP6模式 降水 模拟评估 降尺度 |
| 收稿时间： | 2023/12/12 0:00:00 |
| 修稿时间： | 2024/4/1 0:00:00 |
Evaluation of Precipitation Simulation of Downscaled CMIP6 Models over Xinjiang |
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| HU Ja-hui,SUN Cai-xi,Dong Si-Yan,WANG Bing-lei,OUYANG Hong-xiang,WU Zhi-wen and ZHONG Xiao-yao.Evaluation of Precipitation Simulation of Downscaled CMIP6 Models over Xinjiang[J].Bimonthly of Xinjiang Meteorology,2024,18(5). |
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| Authors: | HU Ja-hui SUN Cai-xi Dong Si-Yan WANG Bing-lei OUYANG Hong-xiang WU Zhi-wen and ZHONG Xiao-yao |
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| Institution: | Xinjiang Climate Center,Xinjiang Climate Center,National Climate Center,Hebei Normal University,Jiangxi Meteorological Station,Guangdong Electric Power Design and Research Institute Co,Ltd,China Energy Engineering Group Corporation,Dongyuan County Meteorological Bureau |
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| Abstract: | Utilizing daily precipitation data from six CMIP6 models, this study employed downscaling techniques to achieve a uniform resolution of 0.25°×0.25°. It evaluated precipitation simulations in the Xinjiang region from 1961 to 2014, focusing on climate state, extremeness, and seasonality through five extreme precipitation indices. Findings show that the downscaled models accurately captured the spatial distribution of Xinjiang''s precipitation, with the highest annual precipitation error under 30 mm and a summer simulation correlation exceeding 0.8. The ACCESS-CM2 model exhibited superior performance, particularly in spring and autumn, where standard deviation ratios ranged between 1.00 and 1.25. Although the ensemble mean simulated the increasing trend in observed precipitation, it underestimated interannual variability. The results suggest a potential link between the precipitation shift in the 1980s and human activities. Furthermore, downscaled data demonstrated superior simulation capabilities for extreme and seasonal precipitation in Xinjiang, outperforming original resolution data in seasonal precipitation accuracy. |
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| Keywords: | CMIP6 model precipitation simulation assessment downscaling |
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