Advances in Atmospheric Sciences

, Volume 35, Issue 8, pp 909–917 | Cite as

Further-Adjusted Long-Term Temperature Series in China Based on MASH

  • Zhen Li
  • Zhongwei YanEmail author
  • Lijuan Cao
  • Phil D. Jones
Open Access
Data Description Article


A set of homogenized monthly mean surface air temperature (SAT) series at 32 stations in China back to the 19th century had previously been developed based on the RHtest method by Cao et al., but some inhomogeneities remained in the dataset. The present study produces a further-adjusted and updated dataset based on the Multiple Analysis of Series for Homogenization (MASH) method. The MASH procedure detects 33 monthly temperature records as erroneous outliers and 152 meaningful break points in the monthly SAT series since 1924 at 28 stations. The inhomogeneous parts are then adjusted relative to the latest homogeneous part of the series. The new data show significant warming trends during 1924–2016 at all the stations, ranging from 0.48 to 3.57°C (100 yr)−1, with a regional mean trend of 1.65°C (100 yr)−1; whereas, the previous results ranged from a slight cooling at two stations to considerable warming, up to 4.5°C (100 yr)−1. It is suggested that the further-adjusted data are a better representation of the large-scale pattern of climate change in the region for the past century. The new data are available online at

Key words

homogenization Multiple Analysis of series for homogenization (MASH) monthly temperature series longterm trend China 


长期的均一化气温观测序列对于气候变化的准确评估和归因至关重要. 然而, 我国多数气象台站不可避免地受到了台站迁址、仪器换型、环境变迁等非自然因素的影响, 造成多数观测序列中存在非均一性. 近几年, 曹丽娟等人利用RHtest方法建立了百年来中国32站均一化逐月气温序列集, 改善了气候变化研究的数据基础. 但这套数据集中仍然存在非均一性, 主要原因有:过于严格的数据处理先决条件, 如:检测到的间断点必须有元数据支持;1950年之前多数台站在订正时无参考序列;不完整的元数据信息, 特别是1950年之前, 这可能使得一些间断点被忽略的可能性进一步增大. 为此, 本研究基于MASH方法对这套数据集中中国中东部28个台站进行了进一步的非均一性订正. 结果表明:1924-2016年间28个台站逐月气温记录中, MASH方法检测到33个月值气温记录异常值和152个有意义的间断点. 根据MASH估计的逐月气温非均一性值, 对5673个月值气温记录做了进一步修正, 调整原则是将气温序列中非均一记录订正到最近时段序列水平上. 通过对比发现, 进一步订正后28个台站1924-2016年年平均气温记录均呈增温趋势且变化趋势范围减小(0.48℃/100年 - 3.57℃/100年), 而之前数据中长沙和南京站呈现出与周边站不一致的降温趋势(−0.23℃/100年- 4.02℃/100年). 进一步订正的数据能更好地代表中国过去百年大尺度气候变化空间格局.


均一化 逐月气温序列 序列均一化多元分析(MASH) 长期趋势 中国 



This work is supported by the Chinese Academy of Sciences International Collaboration Program (Grant No. 134111KYSB20160010), the National Natural Science Foundation of China (Grant Nos. 41505071 and 41475078), and the UK–China Research & Innovation Partnership Fund through the Met Office Climate Science for Service Partnership (CSSP) China as part of the Newton Fund.


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© The Author(s) 2018

Open Access This article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited.

Authors and Affiliations

  • Zhen Li
    • 1
  • Zhongwei Yan
    • 1
    • 2
    Email author
  • Lijuan Cao
    • 3
  • Phil D. Jones
    • 4
    • 5
  1. 1.Key Laboratory of Regional Climate-Environment in Temperate East AsiaInstitute of Atmospheric PhysicsBeijingChina
  2. 2.University of the Chinese Academy of SciencesBeijingChina
  3. 3.National Meteorological Information CenterChina Meteorological AdministrationBeijingChina
  4. 4.Climatic Research UnitUniversity of East AngliaNorwich, NorfolkUK
  5. 5.Center of Excellence for Climate Change Research/Department of MeteorologyKing Abdulaziz UniversityJeddahSaudi Arabia

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