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Detecting Inhomogeneity in Daily Climate Series Using Wavelet Analysis


doi: 10.1007/s00376-008-0157-7

  • 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.
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Manuscript History

Manuscript received: 10 March 2008
Manuscript revised: 10 March 2008
通讯作者: 陈斌, bchen63@163.com
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Detecting Inhomogeneity in Daily Climate Series Using Wavelet Analysis

  • 1. Laboratory of Regional Climate and Environment for Temperate East Asia, Institute of Atmospheric Physics, Chinese Academy of Sciences Beijing 100029;Climatic Research Unit, University of East Anglia, Norwich NR4 7TJ, United Kingdom

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.

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