Detecting inhomogenity in daily climate series using wavelet analysis

Yan, Zhongwei and Jones, Phil D. (2008) Detecting inhomogenity in daily climate series using wavelet analysis. Advances in Atmospheric Sciences, 25. pp. 157-163. ISSN 1861-9533

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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.

Item Type:	Article
Faculty \ School:	Faculty of Science > School of Environmental Sciences
UEA Research Groups:	Faculty of Science > Research Groups > Climatic Research Unit Faculty of Science > Research Groups > Centre for Ocean and Atmospheric Sciences Faculty of Science > Research Groups > Marine and Atmospheric Sciences (former - to 2017) Faculty of Science > Research Groups > Climate, Ocean and Atmospheric Sciences (former - to 2017)
Depositing User:	Rachel Snow
Date Deposited:	02 Mar 2011 10:06
Last Modified:	29 Apr 2025 23:49
URI:	https://ueaeprints.uea.ac.uk/id/eprint/25532
DOI:	10.1007/s00376-008-0157-7

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