Journal of Meteorological Research

, Volume 32, Issue 3, pp 351–366 | Cite as

Projected Changes in Extreme High Temperature and Heat Stress in China

  • Xingcai Liu
  • Qiuhong Tang
  • Xuejun Zhang
  • Siao Sun
Regular Articles


High temperature accompanied with high humidity may result in unbearable and oppressive weather. In this study, future changes of extreme high temperature and heat stress in mainland China are examined based on daily maximum temperature (Tx) and daily maximum wet-bulb globe temperature (Tw). Tw has integrated the effects of both temperature and humidity. Future climate projections are derived from the bias-corrected climate data of five general circulation models under the Representative Concentration Pathways (RCPs) 2.6 and 8.5 scenarios. Changes of hot days and heat waves in July and August in the future (particularly for 2020–50 and 2070–99), relative to the baseline period (1981–2010), are estimated and analyzed. The results show that the future Tx and Tw of entire China will increase by 1.5–5°C on average around 2085 under different RCPs. Future increases in Tx and Tw exhibit high spatial heterogeneity, ranging from 1.2 to 6°C across different regions and RCPs. By around 2085, the mean duration of heat waves will increase by 5 days per annum under RCP8.5. According to Tx, heat waves will mostly occur in Northwest and Southeast China, whereas based on Tw estimates, heat waves will mostly occur over Southeast China and the mean heat wave duration will be much longer than those from Tx. The total extreme hot days (Tx or Tw > 35°C) will increase by 10–30 days. Southeast China will experience the severest heat stress in the near future as extreme high temperature and heat waves will occur more often in this region, which is particularly true when heat waves are assessed based on Tw. In comparison to those purely temperature-based indices, the index Tw provides a new perspective for heat stress assessment in China.

Key words

high temperature wet-bulb globe temperature heat stress climate change 


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We acknowledge the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) coordination team for providing the bias-corrected GCM climate data (


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Copyright information

© The Chinese Meteorological Society and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Xingcai Liu
    • 1
  • Qiuhong Tang
    • 1
    • 2
  • Xuejun Zhang
    • 1
  • Siao Sun
    • 3
  1. 1.Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijingChina
  2. 2.University of Chinese Academy of SciencesBeijingChina
  3. 3.Key Laboratory of Regional Sustainable Development Modeling, Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijingChina

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