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Volume 21 Issue 2

Mar.  2004

Article Contents
Article >  ADVANCES IN ATMOSPHERIC SCIENCES  > 2004 >  21(2): 260-268

Detecting and Adjusting Temporal Inhomogeneity in Chinese Mean Surface Air Temperature Data

  • 1.

    National Meteorological Center,China Meteorological Administration,Beijing 100081,National Meteorological Center,China Meteorological Administration,Beijing 100081,National Meteorological Center,China Meteorological Administration,Beijing 100081,National Climatic Data Center,National Oceanic and Atmospheric Administration,Asheville,NC28801,USA,National Climatic Data Center,National Oceanic and Atmospheric Administration,Asheville,NC28801,USA


doi: 10.1007/BF02915712

  • Adopting the Easterling-Peterson (EP) techniques and considering the reality of Chinese meteorological observations, this paper designed several tests and tested for inhomogeneities in all Chinese historical surface air temperature series from 1951 to 2001. The result shows that the time series have been widely impacted by inhomogeneities resulting from the relocation of stations and changes in local environment such as urbanization or some other factors. Among these factors, station relocations caused the largest magnitude of abrupt changes in the time series, and other factors also resulted in inhomogeneities to some extent. According to the amplitude of change of the difference series and the monthly distribution features of surface air temperatures, discontinuities identified by applying both the E-P technique and supported by China's station history records, or by comparison with other approaches, have been adjusted. Based on the above processing, the most significant temporal inhomogeneities were eliminated, and China's most homogeneous surface air temperature series has thus been created. Results show that the inhomogeneity testing captured well the most important change of the stations, and the adjusted dataset is more reliable than ever. This suggests that the adjusted temperature dataset has great value of decreasing the uncertaities in the study of observed climate change in China.
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    [2] LIU Yonghe, FENG Jinming, MA Zhuguo, 2014: An Analysis of Historical and Future Temperature Fluctuations over China Based on CMIP5 Simulations, ADVANCES IN ATMOSPHERIC SCIENCES, 31, 457-467.  doi: 10.1007/s00376-013-3093-0
    [3] Ming YING, Xiaoqin LU, 2024: The Contribution of United States Aircraft Reconnaissance Data to the China Meteorological Administration Tropical Cyclone Intensity Data: An Evaluation of Homogeneity, ADVANCES IN ATMOSPHERIC SCIENCES, 41, 639-654.  doi: 10.1007/s00376-023-3040-7
    [4] TIAN Di, GUO Yan*, DONG Wenjie, 2015: Future Changes and Uncertainties in Temperature and Precipitation over China Based on CMIP5 Models, ADVANCES IN ATMOSPHERIC SCIENCES, 32, 487-496.  doi: 10.1007/s00376-014-4102-7
    [5] Jeong-Hyeong LEE, Keon-Tae SOHN, 2007: Prediction of Monthly Mean Surface Air Temperature in a Region of China, ADVANCES IN ATMOSPHERIC SCIENCES, 24, 503-508.  doi: 10.1007/s00376-007-0503-1
    [6] CHEN Wei, and LU Riyu, 2014: A Decadal Shift of Summer Surface Air Temperature over Northeast Asia around the Mid-1990s, ADVANCES IN ATMOSPHERIC SCIENCES, 31, 735-742.  doi: 10.1007/s00376-013-3154-4
    [7] MAN Wenmin, and ZHOU Tianjun, 2014: Regional-scale Surface Air Temperature and East Asian Summer Monsoon Changes during the Last Millennium Simulated by the FGOALS-gl Climate System Model, ADVANCES IN ATMOSPHERIC SCIENCES, 31, 765-778.  doi: 10.1007/s00376-013-3123-y
    [8] Chaofan LI, Riyu LU, Philip E. BETT, Adam A. SCAIFE, Nicola MARTIN, 2018: Skillful Seasonal Forecasts of Summer Surface Air Temperature in Western China by Global Seasonal Forecast System Version 5, ADVANCES IN ATMOSPHERIC SCIENCES, 35, 955-964.  doi: 10.1007/s00376-018-7291-7
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    [11] YANG Shili, FENG Jinming, DONG Wenjie, CHOU Jieming, 2014: Analyses of Extreme Climate Events over China Based on CMIP5 Historical and Future Simulations, ADVANCES IN ATMOSPHERIC SCIENCES, 31, 1209-1220.  doi: 10.1007/s00376-014-3119-2
    [12] Qian Weihong, Zhang Henian, Zhu Yafen, Dong-Kyou Lee, 2001: lnterannual and lnterdecadal Variability of East Asian Acas and Their Impact on Temperature of China in Winter Season for the Last Century, ADVANCES IN ATMOSPHERIC SCIENCES, 18, 511-523.  doi: 10.1007/s00376-001-0041-1
    [13] Athanassios A. ARGIRIOU, Zhen LI, Vasileios ARMAOS, Anna MAMARA, Yingling SHI, Zhongwei YAN, 2023: Homogenised Monthly and Daily Temperature and Precipitation Time Series in China and Greece since 1960, ADVANCES IN ATMOSPHERIC SCIENCES, 40, 1326-1336.  doi: 10.1007/s00376-022-2246-4
    [14] REN Guoyu, DING Yihui, ZHAO Zongci, ZHENG Jingyun, WU Tongwen, TANG Guoli, XU Ying, 2012: Recent Progress in Studies of Climate Change in China, ADVANCES IN ATMOSPHERIC SCIENCES, 29, 958-977.  doi: 10.1007/s00376-012-1200-2
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    [16] WANG Shaowu, ZHU Jinhong, CAI Jingning, 2004: Interdecadal Variability of Temperature and Precipitation in China since 1880, ADVANCES IN ATMOSPHERIC SCIENCES, 21, 307-313.  doi: 10.1007/BF02915560
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    • Manuscript History

    Manuscript received: 10 March 2004
    Manuscript revised: 10 March 2004
    通讯作者: 陈斌, bchen63@163.com
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    Detecting and Adjusting Temporal Inhomogeneity in Chinese Mean Surface Air Temperature Data

    • 1. National Meteorological Center,China Meteorological Administration,Beijing 100081,National Meteorological Center,China Meteorological Administration,Beijing 100081,National Meteorological Center,China Meteorological Administration,Beijing 100081,National Climatic Data Center,National Oceanic and Atmospheric Administration,Asheville,NC28801,USA,National Climatic Data Center,National Oceanic and Atmospheric Administration,Asheville,NC28801,USA
    • Manuscript received: 2004-03-10
    • Manuscript revised: 2004-03-10

    Abstract: Adopting the Easterling-Peterson (EP) techniques and considering the reality of Chinese meteorological observations, this paper designed several tests and tested for inhomogeneities in all Chinese historical surface air temperature series from 1951 to 2001. The result shows that the time series have been widely impacted by inhomogeneities resulting from the relocation of stations and changes in local environment such as urbanization or some other factors. Among these factors, station relocations caused the largest magnitude of abrupt changes in the time series, and other factors also resulted in inhomogeneities to some extent. According to the amplitude of change of the difference series and the monthly distribution features of surface air temperatures, discontinuities identified by applying both the E-P technique and supported by China's station history records, or by comparison with other approaches, have been adjusted. Based on the above processing, the most significant temporal inhomogeneities were eliminated, and China's most homogeneous surface air temperature series has thus been created. Results show that the inhomogeneity testing captured well the most important change of the stations, and the adjusted dataset is more reliable than ever. This suggests that the adjusted temperature dataset has great value of decreasing the uncertaities in the study of observed climate change in China.

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