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珠江三角洲地区极端降水时空演变特征
引用本文:邹贤菊,宋晓猛,刘翠善. 珠江三角洲地区极端降水时空演变特征[J]. 水利水运工程学报, 2022, 0(5): 50-60. DOI: 10.12170/20210714002
作者姓名:邹贤菊  宋晓猛  刘翠善
作者单位:1.中国矿业大学 资源与地球科学学院,江苏 徐州 221116
基金项目:国家自然科学基金资助项目(51979271,51609242);中国博士后科学基金资助项目(2018M632333)
摘    要:研究区域极端降水演变对科学应对变化环境下区域水资源利用及防灾减灾具有重要意义。选取气候变化检测指数专家组(ETCCDI)定义的6个极端降水指数(最大持续干旱日数、最大持续降水日数、极端降水日数、极端降水总量、最大日降水量和日降水强度),采用线性趋势法和克里金插值法对珠江三角洲地区极端降水变化进行时空演变分析,并采用交叉小波识别大气环流异常因子(厄尔尼诺-南方涛动、北大西洋涛动、太平洋年代际振荡和印度洋偶极子)与极端降水的相关关系。结果显示:(1)除最大持续降水日数外,各极端降水指数均有不同程度增加,表明珠江三角洲地区极端降水正在增加,但变化不显著;(2)极端降水增加的站点主要集中在区域中部和北部,其中变化显著站点主要位于珠江口北部和区域北部;(3)不同气候态下各极端降水指数总体空间分布相似,但变化趋势空间差异较大,且变化幅度有所增加,表明随着年代际的推移极端降水越来越明显;(4)印度洋偶极子对最大持续干旱日数的影响最显著,而厄尔尼诺-南方涛动对其他极端降水指标的影响最显著。

关 键 词:珠江三角洲地区;极端降水指数   时空演变   大气环流   水资源
收稿时间:2021-07-14

Spatiotemporal changes of extreme precipitation in the Pearl River Delta region
Affiliation:1.School of Resources and Geoscience, China University of Mining and Technology, Xuzhou 221116, China2.Xiamen Water Group Co., Ltd., Xiamen 361008, China3.State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Nanjing Hydraulic Research Institute, Nanjing 210029, China
Abstract:It is of great significance to study the evolution of regional extreme precipitation for scientific response to regional water resources utilization and disaster prevention and reduction under the changing environment. In this work, six extreme precipitation indices defined by the ETCCDI (Expert Team on Climate Change Detection Monitoring and Indices) are selected to analyze the temporal and spatial evolution of extreme precipitation in the Pearl River Delta region by using the linear trend, Kriging interpolation and cross wavelet methods. Besides, the correlation between atmospheric circulation anomalies and extreme precipitation is identified. The results show that: (1) Except for CWD, all the indices have increased by various magnitudes during the period of 1961—2017. It indicates that extreme precipitation is increasing in the Pearl River Delta, but the change is not significant. (2) The stations with increasing trends are mainly located in the central and northern parts of the region, and the stations with a significant change are in the northern part of the Pearl River Estuary and the northern part of the region. (3) The spatial distribution of each index is similar but slightly different for various climate states. The spatial patterns of trends for the four states are significantly different, with the change magnitudes increased from State 1 to State 4. (4) The CDD index is significantly affected by IOD, while the ENSO significantly influences the other indices.
Keywords:
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