Detecting inhomogeneity in daily climate series using wavelet analysis

被引：27

作者：

Yan Zhongwei ^{[1
]}

Jones, Phil D. ^{[2
]}

机构：

[1] Chinese Acad Sci, Inst Atmospher Phys, Lab Reg Climate & Environm Temperate E Asia, Beijing 100029, Peoples R China

[2] Univ E Anglia, Climat Res Unit, Norwich NR4 7TJ, Norfolk, England

来源：

ADVANCES IN ATMOSPHERIC SCIENCES | 2008年 / 25卷 / 02期

关键词：

inhomogeneity; daily meteorological observation; wavelet analysis; climate extremes;

D O I：

10.1007/s00376-008-0157-7

中图分类号：

P4 [大气科学（气象学）];

学科分类号：

0706 ; 070601 ;

摘要：

A wavelet method was applied to detect inhomogeneities in daily meteorological series, data which are being increasingly applied in studies of climate extremes. The wavelet method has been applied to a few well-established long-term daily temperature series back to the 18th century, which have been "homogenized" with conventional approaches. Various types of problems remaining in the series were revealed with the wavelet method. Their influences on analyses of change in climate extremes are discussed. The results have importance for understanding issues in conventional climate data processing and for development of improved methods of homogenization in order to improve analysis of climate extremes based on daily data.

引用

页码：157 / 163

页数：7