Amplified or exaggerated changes in perceived temperature extremes under global warming

  • Shuo Wang
  • Jinxin ZhuEmail author


The perceived temperature has been changing rapidly under global warming, and its related extremes have significant impacts on labor productivity and human health. Although numerous thermal indices have been developed to quantify the perceived temperature, impact assessments have not been conducted comprehensively. The lack of exploring the nonlinearity and linearity inherent in thermal indices will lead to biased conclusions. We conduct a comprehensive investigation of 161 indices to create an ensemble of selected thermal indices that represent the linear and nonlinear relationships of climatic conditions and quantify the changes in the perceived temperature and related extremes. Here we find that the increase in the mean perceived temperature can be strongly exaggerated by using nonlinear indices or linear indices that only consider the combined effect of high temperature and humidity. Wind speed incorporated into the schemes of linear indices can largely offset the increase in the perceived temperature induced by the high relative humidity. These two divergent changes can be further enhanced in future exposure to heat stress. Furthermore, our findings reveal an amplification of heatwave durations induced by the combined effects of multiple variables for all thermal indices. Such an amplification leads to a cascade of relatively short-duration heatwaves evolving into super long-lasting heatwaves which are particularly pronounced over low-latitude areas.


Perceived temperature extremes RCPs Climate change Environmental health 



This research was supported by the National Natural Science Foundation of China (Grant no. 51809223) and the Hong Kong Polytechnic University Start-up Grant (Grant no. 1-ZE8S).

Author contributions

SW and JZ conceived the study and conducted the analysis. Both authors contributed to the writing and the discussion of ideas.

Compliance with ethical standards

Conflict of interest

We declare no competing financial interests.

Supplementary material

382_2019_4994_MOESM1_ESM.docx (2.7 mb)
Supplementary material 1 (DOCX 2775 kb)


  1. Argueso D, Di Luca A, Perkins-Kirkpatrick SE, Evans JP (2016) Seasonal mean temperature changes control future heat waves. Geophys Res Lett 43(14):7653–7660. CrossRefGoogle Scholar
  2. Basu R, Samet JM (2002) Relation between elevated ambient temperature and mortality: a review of the epidemiologic evidence. Epidemiol Rev 24(2):190–202. CrossRefGoogle Scholar
  3. Bobb JF, Peng RD, Bell ML, Dominici F (2014) Heat-related mortality and adaptation to heat in the United States. Environ Health Perspect 122(8):811–816. CrossRefGoogle Scholar
  4. Bongaarts J, O’Neill BC (2018) Global warming policy: is population left out in the cold? Science 361(6403):650–652. CrossRefGoogle Scholar
  5. Carvalho KS, Wang S (2019) Characterizing the Indian Ocean sea level changes and potential coastal flooding impacts under global warming. J Hydrol 569:373–386. CrossRefGoogle Scholar
  6. de Freitas CR, Grigorieva EA (2015) A comprehensive catalogue and classification of human thermal climate indices. Int J Biometeorol 59(1):109–120. CrossRefGoogle Scholar
  7. de Freitas CR, Grigorieva EA (2017) A comparison and appraisal of a comprehensive range of human thermal climate indices. Int J Biometeorol 61(3):487–512. CrossRefGoogle Scholar
  8. Delworth TL, Mahlman JD, Knutson TR (1999) Changes in heat index associated with CO2-induced global warming. Clim Change 43(2):369–386. CrossRefGoogle Scholar
  9. Diffenbaugh NS, Pal JS, Giorgi F, Gao XJ (2007) Heat stress intensification in the Mediterranean climate change hotspot. Geophys Res Lett 34:11. CrossRefGoogle Scholar
  10. Dukesdobos FN (1981) Hazards of heat exposure—a review. Scand J Work Environ Heat 7(2):73–83. CrossRefGoogle Scholar
  11. Dunne JP, Stouffer RJ, John JG (2013) Reductions in labour capacity from heat stress under climate warming. Nat Clim Change 3(6):563–566. CrossRefGoogle Scholar
  12. Fischer EM, Knutti R (2013) Robust projections of combined humidity and temperature extremes. Nat Clim Change 3(2):126–130. CrossRefGoogle Scholar
  13. Fischer EM, Schar C (2010) Consistent geographical patterns of changes in high-impact European heatwaves. Nat Geosci 3(6):398–403. CrossRefGoogle Scholar
  14. Fischer EM, Oleson KW, Lawrence DM (2012) Contrasting urban and rural heat stress responses to climate change. Geophys Res Lett. CrossRefGoogle Scholar
  15. Fischereit J, Schlunzen KH (2018) Evaluation of thermal indices for their applicability in obstacle-resolving meteorology models. Int J Biometeorol 62(10):1887–1900. CrossRefGoogle Scholar
  16. Frieler K, Meinshausen M, von Deimling TS, Andrews T, Forster P (2011) Changes in global-mean precipitation in response to warming, greenhouse gas forcing and black carbon. Geophys Res Lett. CrossRefGoogle Scholar
  17. Gasparrini A et al (2015a) Temporal variation in heat-mortality associations: a multicountry study. Environ Health Perspect 123(11):1200–1207. CrossRefGoogle Scholar
  18. Gasparrini A et al (2015b) Mortality risk attributable to high and low ambient temperature: a multicountry observational study. Lancet 386(9991):369–375. CrossRefGoogle Scholar
  19. Hanna EG, Tait PW (2015) Limitations to thermoregulation and acclimatization challenge human adaptation to global warming. Int J Environ Res Public Health 12(7):8034–8074. CrossRefGoogle Scholar
  20. Horton DE, Johnson NC, Singh D, Swain DL, Rajaratnam B, Diffenbaugh NS (2015) Contribution of changes in atmospheric circulation patterns to extreme temperature trends. Nature 522(7557):465–469. CrossRefGoogle Scholar
  21. Johnson NC, Xie SP, Kosaka Y, Li XC (2018) Increasing occurrence of cold and warm extremes during the recent global warming slowdown. Nat Commun. CrossRefGoogle Scholar
  22. Kovats RS, Hajat S (2008) Heat stress and public health: a critical review. Annu Rev Publ Health 29:41. CrossRefGoogle Scholar
  23. Li JF, Chen YQD, Gan TY, Lau NC (2018) Elevated increases in human-perceived temperature under climate warming. Nat Clim Change 8(1):43–47. CrossRefGoogle Scholar
  24. Lowe D, Ebi KL, Forsberg B (2011) Heatwave early warning systems and adaptation advice to reduce human health consequences of heatwaves. Int J Environ Res Public Health 8(12):4623–4648. CrossRefGoogle Scholar
  25. Matthews TKR, Wilby RL, Murphy C (2017) Communicating the deadly consequences of global warming for human heat stress. Proc Natl Acad Sci USA 114(15):3861–3866. CrossRefGoogle Scholar
  26. Meehl GA, Tebaldi C (2004) More intense, more frequent, and longer lasting heat waves in the 21st century. Science 305(5686):994–997. CrossRefGoogle Scholar
  27. Mora C et al (2017) Global risk of deadly heat. Nat Clim Change 7(7):501–506. CrossRefGoogle Scholar
  28. Sherwood SC, Huber M (2010) An adaptability limit to climate change due to heat stress. Proc Natl Acad Sci USA 107(21):9552–9555. CrossRefGoogle Scholar
  29. Sherwood SC, Ingram W, Tsushima Y, Satoh M, Roberts M, Vidale PL, O’Gorman PA (2010) Relative humidity changes in a warmer climate. J Geophys Res Atmos. CrossRefGoogle Scholar
  30. Shiu CJ, Liu SC, Fu CB, Dai AG, Sun Y (2012) How much do precipitation extremes change in a warming climate? Geophys Res Lett. CrossRefGoogle Scholar
  31. Staiger H, Laschewski G, Grätz A (2012) The perceived temperature—a versatile index for the assessment of the human thermal environment. Part A: Scientific basics. Int J Biometeorol 56(1):165–176. CrossRefGoogle Scholar
  32. Taylor KE, Stouffer RJ, Meehl GA (2012) An overview of CMIP5 and the experiment design. Bull Am Meteorol Soc 93(4):485–498. CrossRefGoogle Scholar
  33. Wang S, Wang Y (2019) Improving probabilistic hydroclimatic projections through high-resolution convection-permitting climate modeling and Markov chain Monte Carlo simulations. Clim Dyn 53(3–4):1613–1636. CrossRefGoogle Scholar
  34. Wang S, Ancell BC, Huang GH, Baetz BW (2018) Improving robustness of hydrologic ensemble predictions through probabilistic pre- and post-processing in sequential data assimilation. Water Resour Res 54(3):2129–2151. CrossRefGoogle Scholar
  35. Wild M, Folini D, Schar C, Loeb N, Dutton EG, Konig-Langlo G (2013) The global energy balance from a surface perspective. Clim Dyn 40(11–12):3107–3134. CrossRefGoogle Scholar
  36. Wild M, Folini D, Henschel F, Fischer N, Muller B (2015) Projections of long-term changes in solar radiation based on CMIP5 climate models and their influence on energy yields of photovoltaic systems. Sol Energy 116:12–24. CrossRefGoogle Scholar
  37. Willett KM, Sherwood S (2012) Exceedance of heat index thresholds for 15 regions under a warming climate using the wet-bulb globe temperature. Int J Climatol 32(2):161–177. CrossRefGoogle Scholar
  38. Willett KM, Gillett NP, Jones PD, Thorne PW (2007) Attribution of observed surface humidity changes to human influence. Nature 449(7163):710-U716. CrossRefGoogle Scholar
  39. Zhang B, Wang S, Wang Y (2019) Copula-based convection-permitting projections of future changes in multivariate drought characteristics 124(14):7460–7483. CrossRefGoogle Scholar
  40. Zhu J, Wang S, Huang G (2019) Assessing climate change impacts on human-perceived temperature extremes and underlying uncertainties. J Geophys Res Atmos 124(7):3800–3821. CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Land Surveying and Geo-InformaticsThe Hong Kong Polytechnic UniversityHong KongChina
  2. 2.The Hong Kong Polytechnic University Shenzhen Research InstituteShenzhenChina

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