Climate Change Research ›› 2021, Vol. 17 ›› Issue (5): 503-513.doi: 10.12006/j.issn.1673-1719.2020.246

• Changes in Climate System • Previous Articles     Next Articles

Effects of data homogenization on the estimates of temperature trend and urbanization bias: taking Beijing area as an example

HE Jia-Jun1(), REN Guo-Yu1,2(), ZHANG Pan-Feng1,3   

  1. 1 Department of Atmospheric Science, China University of Geosciences, Wuhan 430070, China
    2 Laboratory for Climate Studies, National Climate Center, China Meteorological Administration, Beijing 100081, China
    3 School of Tourism and Geographical Sciences, Jilin Normal University, Siping 136000, China
  • Received:2020-10-23 Revised:2020-11-22 Online:2021-09-30 Published:2021-09-28
  • Contact: REN Guo-Yu E-mail:jiajun.he@cug.edu.cn;guoyoo@cma.gov.cn

Abstract:

Inhomogeneity caused by non-climate factors is common in current observation data of surface climate, exerting a great impact on the reliability of climate change monitoring and studies. Based on metadata of observational stations, the non-homogenized (only quality-controlled) monthly mean surface air temperature data series of 20 stations in Beijing were first tested and adjusted for inhomogeneities by the methods of ACMANT and Pairwise Comparisons and RHtestV4 software. The effects of homogenization on the estimates of temperature trend and its urbanization bias were then evaluated. The results show that, in addition to the change points recorded in the metadata, undocumented change points will have a significant effect on the trends of temperature series, especially for the rural stations, which were mostly missed in the previous works of homogenization. The warming trends of the homogenized temperature series for the whole area (all stations), rural stations and urban stations from 1958 to 2018 are 0.27℃/(10 a), 0.10℃/(10 a) and 0.32℃/(10 a), respectively, with an increase of 0.03℃/(10 a), 0.06℃/(10 a) and 0.02℃/(10 a), respectively, compared to the non-homogenized data. Based on the homogenized data, it was estimated that the urbanization effects in the Beijing Observatory data series from 1958 to 2018 is 0.24℃/(10 a), and the urbanization contribution is 70.2%, which are lower than the previous studies of our group. Hence, there are still obvious inhomogeneities and undocumented change points in the existing temperature data in Beijing area, which will have a significant impact on the accurate estimates of regional average temperature change and the urbanization-induced systematic bias of the temperature data series.

Key words: Homogenization, Temperature, Climate change, Trend, Urbanization effects, Beijing

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