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应用生态学报 ›› 2010, Vol. 21 ›› Issue (3): 549-556.

• 研究报告 • 上一篇    下一篇

1959—2006年长白山地区降水序列的多时间尺度分析

胡乃发1,2;王安志1**;关德新1;袁凤辉1;金昌杰1;吴家兵1;王纪军1   

  1. 1中国科学院沈阳应用生态研究所, 沈阳 110016;2中国科学院研究生院,北京 100049
  • 出版日期:2010-03-20 发布日期:2010-03-20

Multiple time scale analysis of precipitation series in Changbai Mountain Region in 1959-2006.

HU Nai-fa1,2|WANG An-zhi1|GUAN De-xin1|YUAN Feng-hui1|JIN Chang-jie1|WU Jia-bing1|WANG Ji-jun1   

  1. 1Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China|2Graduate University of Chinese Academy of Sciences, Beijing
     100049, China
  • Online:2010-03-20 Published:2010-03-20

摘要: 基于长白山地区松江、东岗、长白、和龙、临江和天池6个气象站1959—2006年的月均降水量和年降水量数据,采用Morlet小波分析方法,对1959—2006年长白山地区植被生长季(5—9月)降水量、降雪季(11月至次年4月)降水量和年降水量序列进行多尺度特征分析,并运用Daubechies小波系中的db5小波对各降水序列进行不同层次的分解和低频重构,对重构序列进行了趋势识别和分析.结果表明:研究期间,长白山地区植被生长季降水量存在3~6 a、10~13 a和24~30 a的特征周期;降雪季降水量存在1~2 a、5~7 a和17~20 a的特征周期;年降水存在8~10 a、16~20 a、25~30 a的特征周期;研究区年降水量序列呈现整体下降的趋势.

关键词: 长白山地区, 降水序列, 小波分析, 小波方差, 趋势识别, 冬小麦-夏玉米, 耕作方式, 叶面积, 衰老酶活性

Abstract: Based on the 1959-2006 monthly and annual precipitation data from Songjiang, Donggang, Changbai, Helong, Linjiang, and Tianchi meteorological stations, and by using Morlet wavelet method, a multiple time scale analysis was made on the precipitation series from May to September (vegetation growth season), November to next April (snow season), and the annual in Changbai Mountain Region. The precipitation series was decomposed and low-frequency reconstructed at different levels by using the db5 wavelet of Daubechies wavelets, and the trend of the reconstructed series was identified and analyzed. In 1959-2006, there existed 3-6 years, 10-13 years, and 24-30 years cycles of precipitation series in vegetation growth season, 1-2 years, 5-7 years, and 17-20 years cycles in snow season, and 8-10 years, 16-20 years, and 25-30 years cycles in the annual, and the annual precipitation series showed an overall downward trend.

Key words: Changbai Mountain Region, precipitation series, wavelet analysis, wavelet variance, trend identification, winter wheat-summer maize, tillage method, leaf area, senescence enzyme activity.