1951—2016年沈阳气温和降水的多尺度分析
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摘要
应用集合经验模态分解(EEMD)方法,对1951—2016年沈阳年平均气温和年降水量序列进行多尺度分析,并结合功率谱分析了两要素主要本征模态函数(IMF)分量的周期变化特征。在此基础上,进行了序列重建与对比。结果表明:近66 a来,沈阳年平均气温的变化主要由第1、第2高频分量和趋势项的振荡造成,分别反映了准5 a和准7 a的周期变化以及长期的缓慢增温过程;准14 a的年代际振荡第3分量对沈阳年平均气温变化的作用也不可忽视,而反映更长时间尺度的第4和第5分量在1980年代后与趋势项的变化特征基本一致,表明1980年代后沈阳明显增暖。年降水量的变化主要由第1、第2分量的年际振荡造成,振荡周期分别为准3 a和准5 a,而趋势项则呈现出准64 a的周期变化,总体反映出年降水量在1980年代前后呈现先减后增的变化趋势。与年平均气温序列相比,年降水序列的年代际尺度变化和长期趋势变化的贡献明显偏小。
Based on the monthly average temperature and precipitation at Shenyang station during 1951-2016,the multi-scale temporal characteristics of annual average temperature and precipitation anomaly were analyzed by using the ensemble empirical mode decomposition( EEMD) method,firstly. Then,the periods of main intrinsic mode functions( IMFs) of two elements were discussed by using power spectrum analysis method. And on this basis,the series of two elements based on the components of IMFs were rebuilt and compared. The results show that the variation of annual mean temperature was mainly caused by the oscillation of the first two components with high frequency and the trend component of IMFs in Shenyang during 1951-2016,which reflected the periodic changes with quasi-5-year,quasi-7-year,and long-term upward tendency,respectively. The impact of the third component of IMFs with quasi-14-year period on the annual average temperature wasn't ignorable. In addition,the variations of the fourth and fifth components of IMFs with longer interdecadal time scales were consistent with the trend component after the 1980 s,which indicated the obvious increase of temperature in Shenyang after the 1980 s. The variation of annual precipitation series was mainly caused by the high-frequency oscillations of the first two components of IMFs with quasi-3-year and quasi-5-year periods,respectively,while the trend component with quasi-64-year period of annual precipitation reflected the trend change with the decrease initially and followed by the increase before and after the 1980 s in general. Compared with the temperature series,the contribution of interdecadal and long-term trend change to the precipitation series was limited.
Based on the monthly average temperature and precipitation at Shenyang station during 1951-2016,the multi-scale temporal characteristics of annual average temperature and precipitation anomaly were analyzed by using the ensemble empirical mode decomposition( EEMD) method,firstly. Then,the periods of main intrinsic mode functions( IMFs) of two elements were discussed by using power spectrum analysis method. And on this basis,the series of two elements based on the components of IMFs were rebuilt and compared. The results show that the variation of annual mean temperature was mainly caused by the oscillation of the first two components with high frequency and the trend component of IMFs in Shenyang during 1951-2016,which reflected the periodic changes with quasi-5-year,quasi-7-year,and long-term upward tendency,respectively. The impact of the third component of IMFs with quasi-14-year period on the annual average temperature wasn't ignorable. In addition,the variations of the fourth and fifth components of IMFs with longer interdecadal time scales were consistent with the trend component after the 1980 s,which indicated the obvious increase of temperature in Shenyang after the 1980 s. The variation of annual precipitation series was mainly caused by the high-frequency oscillations of the first two components of IMFs with quasi-3-year and quasi-5-year periods,respectively,while the trend component with quasi-64-year period of annual precipitation reflected the trend change with the decrease initially and followed by the increase before and after the 1980 s in general. Compared with the temperature series,the contribution of interdecadal and long-term trend change to the precipitation series was limited.
引文
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[2] 王闪闪,王素萍,冯建英.2015年全国干旱状况及其影响与成因[J].干旱气象,2016,34(2):382-389.
[3] 王闪闪,王素萍,冯建英.2016年全国干旱状况及其影响与成因[J].干旱气象,2017,35(2):342-351.
[4] 张宇,王素萍,冯建英.2017年全国干旱状况及其影响与成因[J].干旱气象,2018,36(2):331-338.
[5] 周小珊,陈力强,李辑,等.全球气候变暖条件下沈阳若干气候特征的变化[J].高原气象,2005,24(5):823-828.
[6] 殷红,张美玲,辛明月,等.近50年沈阳气温变化与城市化发展的关系[J].生态环境学报,2011,20(3):544-548.
[7] 周小珊,李辑,杨森,等.沈阳近百年的温度变化特征及其环流形势分析[J].气象科学,2004,24(4):424-431.
[8] 刁军,董晓明,姜晓燕.气候变化对沈阳地区大田作物的影响[J].中国农学通报,2012,28(23):266-270.
[9] 邹旭东,杨洪斌,张云海,等.1951—2012 年沈阳市气象条件变化及其与空气污染的关系分析[J].生态环境学报,2015,24(1):76-83.
[10] 孟鹏,安昕.沈阳市不同时间尺度降水趋势及突变研究[J].中国农学通报,2014,30(33):256-262.
[11] HUANG N E,SHEN Z,LONG S R,et al.The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis[J].Proceedings of the Royal Society A:Mathematical,Physical and Engineering Sciences,1998,454(1971):903-995.
[12] WU Z H,HUANG N E.Ensemble empirical mode decomposition:A noise-assisted data analysis method[J].Advances in Adaptive Data Analysis,2008,1(1):1-41.
[13] 魏凤英.现代气候统计诊断与预测技术[M].北京:气象出版社,1985.
[14] 贺伟,布仁仓,熊在平,等.1961—2005年东北地区气温和降水变化趋势[J].生态学报,2013,33(2):519-531.
[15] 徐保梁,杨庆,马柱国.全球不同空间尺度陆地年降水的年代尺度变化特征[J].大气科学,2017,41(3):593-602.
[16] 刘莉红,郑祖光,琚建华.基于EMD方法的我国年气温和东部年降水量序列的振荡模态分析[J].高原气象,2008,27(5):1060-1065.
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