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Projected Changes in Extreme High Temperature and Heat Stress in China

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Abstract

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.

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References

  • American College of Sports Medicine (ACSM), 1984: Prevention of thermal injuries during distance running. Phys. Sportsmed., 12, 43–51, doi: 10.1080/00913847.1984.11701899.

  • Barriopedro, D., E. M. Fischer, and J. Luterbacher, 2011: The hot summer of 2010: Redrawing the temperature record map of Europe. Science, 332, 220–224, doi: 10.1126/science. 1201224.

  • Budd, G. M., 2008: Wet-bulb globe temperature (WBGT)-Its history and its limitations. J. Sci. Med. Sport, 11, 20–32, doi: 10.1016/j.jsams.2007.07.003.

  • Chen K., J. Bi, J. Chen, et al., 2015: Influence of heat wave definitions to the added effect of heat waves on daily mortality in Nanjing, China. Sci. Total Environ., 506–507, 18–25, doi: 10.1016/j.scitotenv.2014.10.092.

    Article  Google Scholar 

  • Chen Y., and Y. Li, 2017: An inter-comparison of three heat wave types in China during 1961–2010: Observed basic features and linear trends. Sci. Rep., 7, 45619, doi: 10.1038/srep45619.

    Article  Google Scholar 

  • Chen Y. Y., K. Yang, J. He, et al., 2011: Improving land surface temperature modeling for dry land of China. J. Geophys. Res., 116, D20104, doi: 10.1029/2011JD015921.

    Article  Google Scholar 

  • China Meteorological Administration, 2015: QX/T 280–2015 Monitoring indices of high temperature extremes. Available at http://www.cmastd.cn/standardView.jspx?id=2103. Accessed on 26 March 2017. (in Chinese).

    Google Scholar 

  • Debele B., R. Srinivasan, and J. Y. Parlange, 2007: Accuracy evaluation of weather data generation and disaggregation methods at finer timescales. Adv. Water Res., 30, 1286–1300, doi: 10.1016/j.advwatres.2006.11.009.

    Article  Google Scholar 

  • Ding T., and W. H. Qian, 2011: Geographical patterns and temporal variations of regional dry and wet heatwave events in China during 1960–2008. Adv. Atmos. Sci., 28, 322–337, doi: 10.1007/s00376-010-9236-7.

    Article  Google Scholar 

  • Elliott J., D. Deryng, C. Müller, et al., 2014: Constraints and potentials of future irrigation water availability on agricultural production under climate change. Proc. Natl. Acad. Sci. USA, 111, 3239–3244, doi: 10.1073/pnas.1222474110.

    Article  Google Scholar 

  • Fischer E. M., and R. Knutti, 2013: Robust projections of combined humidity and temperature extremes. Nat. Climate Change, 3, 126–130, doi: 10.1038/nclimate1682.

    Article  Google Scholar 

  • Grazzini F., L. Ferranti, F. Lalaurette, et al., 2003: The exceptional warm anomalies of summer 2003. ECMWF Newslett., 99, 2–9.

    Google Scholar 

  • Guo X. J., J. B. Huang, Y. Luo, et al., 2017: Projection of heat waves over China for eight different global warming targets using 12 CMIP5 models. Theor. Appl. Climatol., 128, 507–522, doi: 10.1007/s00704-015-1718-1.

    Article  Google Scholar 

  • Guo Y. J., S. Q. Zhang, J. H. Yan, et al., 2016: A comparison of atmospheric temperature over China between radiosonde observations and multiple reanalysis datasets. J. Meteor. Res., 30, 242–257, doi: 10.1007/s13351-016-5169-0.

    Article  Google Scholar 

  • Hauser M., R. Orth, and S. I. Seneviratne, 2016: Role of soil moisture versus recent climate change for the 2010 heat wave in western Russia. Geophys. Res. Lett., 43, 2819–2826, doi: 10.1002/2016GL068036.

    Article  Google Scholar 

  • Hempel S., K. Frieler, L. Warszawski, et al., 2013: A trend-preserving bias correction—the ISI-MIP approach. Earth Syst. Dyn., 4, 219–236, doi: 10.5194/esd-4-219-2013.

    Article  Google Scholar 

  • Herring S. C., A. Hoell, M. P. Hoerling, et al., 2016: Explaining extreme events of 2015 from a climate perspective. Bull. Amer. Meteor. Soc., 97, S1–S145, doi: 10.1175/BAMS-ExplainingExtremeEvents2015.1.

    Google Scholar 

  • Hirschi M., S. I. Seneviratne, V. Alexandrov, et al., 2011: Observational evidence for soil-moisture impact on hot extremes in southeastern Europe. Nat. Geosci., 4, 17–21, doi: 10.1038/ngeo1032.

    Article  Google Scholar 

  • IPCC, 2013: Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. T. F. Stocker, et al., Eds., Cambridge University Press, Cambridge, United Kingdom, New York, NY, USA, 1535 pp.

  • Leng G. Y., Q. H. Tang, S. Z. Huang, et al., 2016: Assessments of joint hydrological extreme risks in a warming climate in China. Int. J. Climatol., 36, 1632–1642, doi: 10.1002/joc.4447.

    Article  Google Scholar 

  • Li Y., Y. H. Ding, and W. J. Li, 2017: Observed trends in various aspects of compound heat waves across China from 1961 to 2015. J. Meteor. Res., 31, 455–467, doi: 10.1007/s13351-017-6150-2.

    Article  Google Scholar 

  • Li Y. H., Y. B. Cheng, G. Q. Cui, et al., 2014: Association between high temperature and mortality in metropolitan areas of four cities in various climatic zones in China: A time-series study. Environ. Health, 13, 65, doi: 10.1186/1476-069X-13-65.

    Article  Google Scholar 

  • Liu X. C., Q. H. Tang, X. J. Zhang, et al., 2017: Spatially distinct effects of preceding precipitation on heat stress over eastern China. Environ. Res. Lett., 12, 115010, doi: 10.1088/1748-9326/aa88f8.

    Article  Google Scholar 

  • Lorenz R., D. Argüeso, M. G. Donat, et al., 2016: Influence of land–atmosphere feedbacks on temperature and precipitation extremes in the GLACE-CMIP5 ensemble. J. Geophys. Res., 121, 607–623, doi: 10.1002/2015JD024053.

    Google Scholar 

  • McSweeney C. F., and R. G. Jones, 2016: How representative is the spread of climate projections from the 5 CMIP5 GCMs used in ISI-MIP? Climate Serv., 1, 24–29, doi: 10.1016/j.cliser.2016.02.001.

    Article  Google Scholar 

  • Miao C. Y., Q. H. Sun, D. X. Kong, et al., 2016: Record-breaking heat in Northwest China in July 2015: Analysis of the severity and underlying causes. Bull. Amer. Meteor. Soc., 97, S97–S101, doi: 10.1175/BAMS-D-16-0142.1.

    Article  Google Scholar 

  • Mishra V., A. R. Ganguly, B. Nijssen, et al., 2015: Changes in observed climate extremes in global urban areas. Environ. Res. Lett., 10, 024005, doi: 10.1088/1748-9326/10/2/024005.

    Article  Google Scholar 

  • Mitchell D., 2016: Human influences on heat-related health indicators during the 2015 Egyptian heat wave. Bull. Amer. Meteor. Soc., 97, S70–S74, doi: 10.1175/BAMS-D-16-0132.1.

    Article  Google Scholar 

  • Mueller B., X. B. Zhang, and F. W. Zwiers, 2016: Historically hottest summers projected to be the norm for more than half of the world’s population within 20 years. Environ. Res. Lett., 11, 044011, doi: 10.1088/1748-9326/11/4/044011.

    Article  Google Scholar 

  • Murray F. W., 1967: On the computation of saturation vapor pressure. J. Appl. Meteor., 6, 203–204, doi: 10.1175/1520-0450(1967)006<0203:otcosv>2.0.co;2.

    Article  Google Scholar 

  • Qi L., and Y. Q. Wang, 2012: Changes in the observed trends in extreme temperatures over China around 1990. J. Climate, 25, 5208–5222, doi: 10.1175/jcli-d-11-00437.1.

    Article  Google Scholar 

  • Schar C., P. L. Vidale, D. Lüthi, et al., 2004: The role of increasing temperature variability in European summer heatwaves. Nature, 427, 332–336, doi: 10.1038/nature02300.

    Article  Google Scholar 

  • Schewe J., J. Heinke, D. Gerten, et al., 2014: Multimodel assessment of water scarcity under climate change. Proc. Natl. Acad. Sci. USA, 111, 3245–3250, doi: 10.1073/pnas.1222 460110.

    Article  Google Scholar 

  • Seneviratne S. I., T. Corti, E. L. Davin, et al., 2010: Investigating soil moisture–climate interactions in a changing climate: A review. Earth Sci. Rev., 99, 125–161, doi: 10.1016/j.earscirev.2010.02.004.

    Article  Google Scholar 

  • Sherwood S. C., and M. Huber, 2010: An adaptability limit to climate change due to heat stress. Proc. Natl. Acad. Sci. USA, 107, 9552–9555, doi: 10.1073/pnas.0913352107.

    Article  Google Scholar 

  • Steadman R. G., 1979: The assessment of sultriness. Part I: A temperature–humidity index based on human physiology and clothing science. J. Appl. Meteor., 18, 861–873, doi: 10.1175/1520-0450(1979)018<0861:taospi>2.0.co;2.

    Article  Google Scholar 

  • Steadman R. G., 1984: A universal scale of apparent temperature. J. Climate Appl. Meteor., 23, 1674–1687, doi: 10.1175/1520-0450(1984)023<1674:ausoat>2.0.co;2.

    Article  Google Scholar 

  • Sun Q. H., C. Y. Miao, A. AghaKouchak, et al., 2017: Unraveling anthropogenic influence on the changing risk of heat waves in China. Geophys. Res. Lett., 44, 5078–5085, doi: 10.1002/2017GL073531.

    Article  Google Scholar 

  • Sun Y., L. C. Song, H. Yin, et al., 2016: Human influence on the 2015 extreme high temperature events in western China. Bull. Amer. Meteor. Soc., 97, S102–S106, doi: 10.1175/bams-d-16-0158.1.

    Article  Google Scholar 

  • Sun Y., X. B. Zhang, F. W. Zwiers, et al., 2014: Rapid increase in the risk of extreme summer heat in eastern China. Nat. Climate Change, 4, 1082–1085, doi: 10.1038/nclimate2410.

    Article  Google Scholar 

  • Tang Q. H., X. J. Zhang, and J. A. Francis, 2014: Extreme summer weather in northern mid-latitudes linked to a vanishing cryosphere. Nat. Climate Change, 4, 45–50, doi: 10.1038/nclimate2065.

    Article  Google Scholar 

  • Wang J. X. L., and D. J. Gaffen, 2001: Trends in extremes of surface humidity, temperature, and summertime heat stress in China. Adv. Atmos. Sci., 18, 742–751.

    Google Scholar 

  • Warszawski L., K. Frieler, V. Huber, et al., 2014: The Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP): Project framework. Proc. Nat. Acad. Sci. USA, 111, 3228–3232, doi: 10.1073/pnas.1312330110.

    Article  Google Scholar 

  • Weedon G. P., S. Gomes, P. Viterbo, et al., 2011: Creation of the WATCH forcing data and its use to assess global and regional reference crop evaporation over land during the twentieth century. J. Hydrometeor., 12, 823–848, doi: 10.1175/2011jhm1369.1.

    Article  Google Scholar 

  • Wehner M., D. Stone, H. Krishnan, et al., 2016: The deadly combination of heat and humidity in India and Pakistan in summer 2015. Bull. Amer. Meteor. Soc., 97, S81–S86, doi: 10.1175/BAMS-D-16-0145.1.

    Article  Google Scholar 

  • Willett K. M., and S. Sherwood, 2012: Exceedance of heat index thresholds for 15 regions under a warming climate using the wet-bulb globe temperature. Int. J. Climatol., 32, 161–177, doi: 10.1002/joc.2257.

    Article  Google Scholar 

  • Yan Z., P. D. Jones, T. D. Davies, et al., 2002: Trends of extreme temperatures in Europe and China based on daily observations. Climatic Change, 53, 355–392, doi: 10.1023/A:1014939413284.

    Article  Google Scholar 

  • Yang K., J. He, W. J. Tang, et al., 2010: On downward shortwave and longwave radiations over high altitude regions: Observation and modeling in the Tibetan Plateau. Agric. For. Meteor., 150, 38–46, doi: 10.1016/j.agrformet.2009.08.004.

    Article  Google Scholar 

  • Yin Y., Q. Tang, and X. Liu, 2015: A multi-model analysis of change in potential yield of major crops in China under climate change. Earth Syst. Dyn., 6, 45–59, doi: 10.5194/esd-6-45-2015.

    Article  Google Scholar 

  • Yin Y. Y., Q. H. Tang, L. X. Wang, et al., 2016: Risk and contributing factors of ecosystem shifts over naturally vegetated land under climate change in China. Sci. Rep., 6, 20905, doi: 10.1038/srep20905.

    Article  Google Scholar 

  • You Q. L., J. Z. Min, K. Fraedrich, et al., 2014: Projected trends in mean, maximum, and minimum surface temperature in China from simulations. Glob. Planet. Change, 112, 53–63, doi: 10.1016/j.gloplacha.2013.11.006.

    Article  Google Scholar 

  • You Q. L., Z. H. Jiang, L. Kong, et al., 2017: A comparison of heat wave climatologies and trends in China based on multiple definitions. Climate Dyn., 48, 3975–3989, doi: 10.1007/s00382-016-3315-0.

    Article  Google Scholar 

  • Zhai P. M., and X. H. Pan, 2003: Trends in temperature extremes during 1951–1999 in China. Geophys. Res. Lett., 30, 1913, doi: 10.1029/2003gl018004.

    Article  Google Scholar 

  • Zhang J. Y., and L. Y. Wu, 2011: Land–atmosphere coupling amplifies hot extremes over China. Chin. Sci. Bull., 56, 3328–3332, doi: 10.1007/s11434-011-4628-3.

    Article  Google Scholar 

  • Zhang Q., M. Z. Xiao, V. P. Singh, et al., 2015: Observational evidence of summer precipitation deficit-temperature coupling in China. J. Geophys. Res., 120, 10040–10049, doi: 10.1002/2015JD023830.

    Google Scholar 

  • Zhang X. J., Q. H. Tang, M. Pan, et al., 2014: A long-term land surface hydrologic fluxes and states dataset for China. J. Hydrometeor., 15, 2067–2084, doi: 10.1175/JHM-D-13-0170.1.

    Article  Google Scholar 

  • Zhang Y. J., Z. Q. Gao, Z. T. Pan, et al., 2017: Spatiotemporal variability of extreme temperature frequency and amplitude in China. Atmos. Res., 185, 131–141, doi: 10.1016/j.atmosres.2016.10.018.

    Article  Google Scholar 

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Acknowledgments

We acknowledge the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) coordination team for providing the bias-corrected GCM climate data (https://www.isimip.org/).

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Correspondence to Qiuhong Tang.

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Supported by the National Natural Science Foundation of China (41730645 and 41425002), Key Research Program of the Chinese Academy of Sciences (ZDRW-ZS-2017-4), National Youth Top-Notch Talent Support Program in China, and Chinese Postdoctoral Science Foundation (2016M601117).

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Liu, X., Tang, Q., Zhang, X. et al. Projected Changes in Extreme High Temperature and Heat Stress in China. J Meteorol Res 32, 351–366 (2018). https://doi.org/10.1007/s13351-018-7120-z

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