Detecting inhomogenity in daily climate series using wavelet analysis

Zhongwei Yan, Phil D. Jones

Research output: Contribution to journalArticlepeer-review

Abstract

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.
Original languageEnglish
Pages (from-to)157-163
Number of pages7
JournalAdvances in Atmospheric Sciences
Volume25
DOIs
Publication statusPublished - Mar 2008

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