太湖流域降水变化及与组合大气环流的关系

吴舒祺; 么嘉棋; 候文星; 阿多; 赵文吉

引用本文:	吴舒祺,么嘉棋,候文星,等.太湖流域降水变化及与组合大气环流的关系[J].灌溉排水学报,2022,():-.
	Wu Shuqi,Yao Jiaqi,Hou wenxing,et al.太湖流域降水变化及与组合大气环流的关系[J].灌溉排水学报,2022,():-.

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太湖流域降水变化及与组合大气环流的关系
吴舒祺¹, 么嘉棋², 候文星¹, 阿多³, 赵文吉¹
1.首都师范大学资源环境与旅游学院;2.山东科技大学测绘与空间信息学院;3.应急管理部国家减灾中心

摘要:

【目的】为研究区域降水变化及与大气环流的多尺度效应。【方法】采用MK(Mann Kendall)、MMK(Modified Mann Kendall)趋势检验法以及小波相干 (Wavelet Coherence, WTC)、多小波相干分析(Multiple Wavelet Coherence, MWC),对太湖流域1960—2020年30个气象站点的降水的变化及与单个和组合大气环流因子的多尺度振荡进行分析。【结果】主要结果如下：(1)MMK及MK的趋势值在年尺度降水及季节尺度降水的空间分布大致相似,但显著性存在差异。年降水上升趋势最大,而冬季降水上升趋势最小。MMK可以检测出MK没有检测到的显著性,尤其对于春季降水。(2)WTC结果表明,湖流域降水与大气环流因子具有复杂的非线性关系,在不同时域中具有明显差异。(3)从单要素来看,EASM是太湖流域最具影响力的遥相关；在多要素组合中,Prep-AO-PDO-ENSO-EASM-DMI组合对流域降水影响最大。【结论】单独的主导遥相关并不能很好解释降水与大气环流的关系,具有最高显著功率数百分比(POPS)的大气环流组合可作为解释降水变化的最佳组合。

关键词: MMK趋势检验法;多小波相干;组合大气环流;多尺度效应;显著功率百分比

DOI：

分类号:P426.6; P434

基金项目:国家重点研发计划课题(2017YFC1502901)

Variation of precipitation in the Taihu Lake Basin and its relationship with the combined atmospheric circulation

Wu Shuqi¹, Yao Jiaqi², Hou wenxing¹, A Duo³, Zhao Wenji¹

1.College of Resource Environment and Tourism,Capital Normal University;2.College of Geodesy and Geomatics,Shandong University of Science and Technology;3.National Disaster Reduction Center of China

Abstract:

[Objective]To study regional precipitation variation and its multi-scale effects with atmospheric circulation. [Method]Using MK (Mann Kendall), MMK (Modified Mann Kendall), wavelet coherence (WTC), multiple wavelet coherence (MWC) to analyze changes of precipitation at 30 meteorological stations in the Taihu Lake Basin(TLB) from 1960 to 2020 and the multi-scale oscillations with single and combined atmospheric circulation. [Result]The main results are as follows: (1) The spatial distributions of the trend values ??of MMK and MK are similar in the annual and seasonal scale, but significance differs. The annual precipitation in TLB has the largest upward trend, while precipitation in winter had the smallest upward trend. MMK can detect significance that MK does not, especially for spring precipitation. (2) The WTC showed that precipitation and atmospheric circulation had a complex nonlinear relationship, but there were notable differences across various time domains.(3) Of all single variables, the EASM was the most influential teleconnection in the TLB. Among the multivariate combinations, Prep-AO-PDO-ENSO-EASM-DMI had the greatest impact on precipitation. [Conclusion]The dominant tele-correlation alone cannot explain the relationship between precipitation and atmospheric circulation, and the combination of atmospheric circulation with the highest percentage of significant power (POPS) can be used as the best combination to explain precipitation changes.

Key words: MMK trend test method; multi-wavelet coherence; combined atmospheric circulation; multi-scale effect; percentage of significant power