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Volume 25 Issue 2

Mar.  2008

Article Contents
Article >  ADVANCES IN ATMOSPHERIC SCIENCES  > 2008 >  25(2): 157-163

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


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.
  • [1] HU Zhiqun, and LIU Liping, 2014: Applications of Wavelet Analysis in Differential Propagation Phase Shift Data De-noising, ADVANCES IN ATMOSPHERIC SCIENCES, 31, 825-835.  doi: 10.1007/s00376-013-3095-y
    [2] Yan Zhongwei, Yang Chi, Phil Jones, 2001: Influence of Inhomogeneity on the Estimation of Mean and Extreme Temperature Trends in Beijing and Shanghai, ADVANCES IN ATMOSPHERIC SCIENCES, 18, 309-322.  doi: 10.1007/BF02919312
    [3] Tianjun ZHOU, Wenxia ZHANG, Lixia ZHANG, Robin CLARK, Cheng QIAN, Qinghong ZHANG, Hui QIU, Jie JIANG, Xing ZHANG, 2022: 2021: A Year of Unprecedented Climate Extremes in Eastern Asia, North America, and Europe, ADVANCES IN ATMOSPHERIC SCIENCES, 39, 1598-1607.  doi: 10.1007/s00376-022-2063-9
    [4] Hengyi WENG, 2012: Impacts of Multi-Scale Solar Activity on Climate. Part I: Atmospheric Circulation Patterns and Climate Extremes, ADVANCES IN ATMOSPHERIC SCIENCES, 29, 867-886.  doi: 10.1007/s00376-012-1238-1
    [5] Huanhuan ZHU, Zhihong JIANG, Juan LI, Wei LI, Cenxiao SUN, Laurent LI, 2020: Does CMIP6 Inspire More Confidence in Simulating Climate Extremes over China?, ADVANCES IN ATMOSPHERIC SCIENCES, 37, 1119-1132.  doi: 10.1007/s00376-020-9289-1
    [6] QIAN Cheng, YAN Zhongwei, Zhaohua WU, FU Congbin, TU Kai, 2011: Trends in Temperature Extremes in Association with Weather-Intraseasonal Fluctuations in Eastern China, ADVANCES IN ATMOSPHERIC SCIENCES, 28, 297-309.  doi: 10.1007/s00376-010-9242-9
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    [8] Xiaojuan ZHANG, Fei ZHENG, Jiang ZHU, Xingrong CHEN, 2022: Observed Frequent Occurrences of Marine Heatwaves in Most Ocean Regions during the Last Two Decades, ADVANCES IN ATMOSPHERIC SCIENCES, 39, 1579-1587.  doi: 10.1007/s00376-022-1291-3
    [9] Lonnie Hudgins, Jianping Huang, 1996: Bivariate Wavelet Analysis of Asia Monsoon and ENSO, ADVANCES IN ATMOSPHERIC SCIENCES, 13, 299-312.  doi: 10.1007/BF02656848
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    [11] LI Qingxiang, LIU Xiaoning, ZHANG Hongzheng, Thomas C. PETERSON, David R. EASTERLING, 2004: Detecting and Adjusting Temporal Inhomogeneity in Chinese Mean Surface Air Temperature Data, ADVANCES IN ATMOSPHERIC SCIENCES, 21, 260-268.  doi: 10.1007/BF02915712
    [12] Kate M. WILLETT, 2023: HadISDH.extremes Part I: A Gridded Wet Bulb Temperature Extremes Index Product for Climate Monitoring, ADVANCES IN ATMOSPHERIC SCIENCES, 40, 1952-1967.  doi: 10.1007/s00376-023-2347-8
    [13] Huqiang ZHANG, LI Yaohui, GAO Xuejie, 2009: Potential Impacts of Land-Use on Climate Variability and Extremes, ADVANCES IN ATMOSPHERIC SCIENCES, 26, 840-854.  doi: 10.1007/s00376-009-8047-1
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    [16] Chengjun XIE, Tongwen WU, Jie ZHANG, Kalli FURTADO, Yumeng ZHOU, Yanwu ZHANG, Fanghua WU, Weihua JIE, He ZHAO, Mengzhe ZHENG, 2023: Spatial Inhomogeneity of Atmospheric CO2 Concentration and Its Uncertainty in CMIP6 Earth System Models, ADVANCES IN ATMOSPHERIC SCIENCES, 40, 2108-2126.  doi: 10.1007/s00376-023-2294-4
    [17] Peihua QIN, Zhenghui XIE, Jing ZOU, Shuang LIU, Si CHEN, 2021: Future Precipitation Extremes in China under Climate Change and Their Physical Quantification Based on a Regional Climate Model and CMIP5 Model Simulations, ADVANCES IN ATMOSPHERIC SCIENCES, 38, 460-479.  doi: 10.1007/s00376-020-0141-4
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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
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

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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
    • Manuscript received: 2008-03-10
    • Manuscript revised: 2008-03-10

    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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