Extreme heat under global warming is a concerning issue for the growing tropical population. However, model projections of extreme temperatures, a widely used metric for extreme heat, are uncertain on regional scales. In addition, humidity needs to be taken into account to estimate the health impact of extreme heat. Here we show that an integrated temperature–humidity metric for the health impact of heat, namely, the extreme wet-bulb temperature (TW), is controlled by established atmospheric dynamics and thus can be robustly projected on regional scales. For each 1 °C of tropical mean warming, global climate models project extreme TW (the annual maximum of daily mean or 3-hourly values) to increase roughly uniformly between 20° S and 20° N latitude by about 1 °C. This projection is consistent with theoretical expectation based on tropical atmospheric dynamics, and observations over the past 40 years, which gives confidence to the model projection. For a 1.5 °C warmer world, the probable (66% confidence interval) increase of regional extreme TW is projected to be 1.33–1.49 °C, whereas the uncertainty of projected extreme temperatures is 3.7 times as large. These results suggest that limiting global warming to 1.5 °C will prevent most of the tropics from reaching a TW of 35 °C, the limit of human adaptation.
Subscribe to Journal
Get full journal access for 1 year
only $4.92 per issue
All prices are NET prices.
VAT will be added later in the checkout.
Tax calculation will be finalised during checkout.
Rent or Buy article
Get time limited or full article access on ReadCube.
All prices are NET prices.
CMIP5 model data provided by the World Climate Research Programme’s Working Group on Coupled Modelling, and climate modelling groups can be accessed at https://esgf-node.llnl.gov/projects/cmip5. ERA-Interim data provided by European Centre for Medium-Range Weather Forecast (ECMWF) can be accessed at http://go.nature.com/3piVLPO. HadISD global sub-daily station dataset (v188.8.131.52909p) provided by Met Office Hadley Centre can be accessed at https://www.metoffice.gov.uk/hadobs/hadisd. HadISST data provided by the Met Office Hadley Centre can be accessed at https://www.metoffice.gov.uk/hadobs/hadisst.
The computer code used in this paper is available from the corresponding author.
Mahlstein, I., Knutti, S., Solomon, S. & Portmann, R. W. Early onset of significant local warming in low latitude countries. Environ. Res. Lett. 6, 034009 (2011).
Coumou, D., Robinson, A. & Rahmstorf, S. Global increase in record-breaking monthly-mean temperatures. Clim. Change 118, 771–782 (2013).
Hoegh-Guldberg, O. et al. in Special Report on Global Warming of 1.5 °C (eds Masson-Delmotte, V. et al.) Ch. 3 (IPCC, 2018).
World Population Prospects 2019: Highlights ST/ESA/SER.A/423 (United Nations, Department of Economic and Social Affairs, Population Division, 2019).
Vogel, M. et al. Regional amplification of projected changes in extreme temperatures strongly controlled by soil moisture–temperature feedbacks. Geophys. Res. Lett. 44, 1511–1519 (2017).
Kovats, R. S. & Hajat, S. Heat stress and public health: a critical review. Annu. Rev. Public Health 29, 41–55 (2008).
Mitchell, D. et al. Attributing human mortality during extreme heat waves to anthropogenic climate change. Environ. Res. Lett. 11, 074006 (2016).
Hardy, J. D., Du Bois, E. F. & Soderstrom, G. F. Basal metabolism, radiation, convection and vaporization at temperatures of 22 to 35 °C. J. Nutr. 15, 477–497 (1938).
Hardy, J. D. & Stolwijk, J. A. Partitional calorimetric studies of man during exposures to thermal transients. J. Appl. Physiol. 21, 1799–1806 (1966).
Mora, C. et al. Global risk of deadly heat. Nat. Clim. Change 7, 501–505 (2017).
Sherwood, S. C. How important is humidity in heat stress? J. Geophys. Res. Atmos. 123, 808–810 (2018).
Delworth, T. L., Mahlman, J. D. & Knutson, T. R. Changes in heat index associated with CO2-induced global warming. Clim. Change 43, 369–386 (1999).
Willett, K. M. & Sherwood, S. Exceedance of heat index thresholds for 15 regions under a warming climate using the wet-bulb globe temperature. Int. J. Climatol. 32, 161–177 (2012).
Fischer, E. M. & Knutti, R. Robust projections of combined humidity and temperature extremes. Nat. Clim. Change 3, 126–130 (2013).
Coffel, E. D., Horton, R. M., Winter, J. M. & Mankin, J. S. Nonlinear increases in extreme temperatures paradoxically dampen increases in extreme humid-heat. Environ. Res. Lett. 14, 084003 (2019).
Sherwood, S. C. & Huber, M. An adaptability limit to climate change due to heat stress. Proc. Natl Acad. Sci. USA 107, 9552–9555 (2010).
Ergonomics of the Thermal Environment—Assessment of Heat Stress Using the WBGT (Wet Bulb Globe Temperature) Index ISO Standard No. 7243:2017 (International Organization for Standardization, 2017); https://www.iso.org/standard/67188.html
Byrne, M. P. & O’Gorman, P. A. Land–ocean warming contrast over a wide range of climates: convective quasi-equilibrium theory and idealized simulations. J. Clim. 26, 4000–4016 (2013).
Byrne, M. P. & O’Gorman, P. A. Link between land–ocean warming contrast and surface relative humidities in simulations with coupled climate models. Geophys. Res. Lett. 40, 5223–5227 (2013).
Byrne, M. P. & O’Gorman, P. A. Trends in continental temperature and humidity directly linked to ocean warming. Proc. Natl Acad. Sci. USA 115, 4863–4868 (2018).
Zhang, Y. & Fueglistaler, S. How tropical convection couples high moist static energy over land and ocean. Geophys. Res. Lett. 47, e2019GL086387 (2020).
Taylor, K. E., Stouffer, R. J. & Meehl, G. A. An overview of CMIP5 and the experiment design. Bull. Am. Meteorol. Soc. 93, 485–498 (2012).
Sobel, A. H., Held, I. M. & Bretherton, C. S. The ENSO signal in tropical tropospheric temperature. J. Clim. 15, 2702–2706 (2002).
Flannaghan, T. J. et al. Tropical temperature trends in Atmospheric General Circulation Model simulations and the impact of uncertainties in observed SSTs. J. Geophys. Res. 119, 327–337 (2014).
Fueglistaler, S. Observational evidence for two modes of coupling between sea surface temperatures, tropospheric temperature profile and shortwave cloud radiative effect in the tropics. Geophys. Res. Lett. 46, 9890–9898 (2019).
Pal, J. S. & Eltahir, E. A. B. Future temperature in southwest Asia projected to exceed a threshold for human adaptability. Nat. Clim. Change 6, 197–200 (2016).
Im, E., Pal, J. S. & Eltahir, E. A. B. Deadly heat waves projected in the densely populated agricultural regions of South Asia. Sci. Adv. 3, e1603322 (2017).
Dee, D. P. et al. The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Q. J. R. Meteorol. Soc. 137, 553–597 (2011).
Dunn, R. J. H., Willett, K. M., Parker, D. E. & Mitchell, L. Expanding HadISD: quality-controlled, sub-daily station data from 1931. Geosci. Instrum. Methods Data Syst. 5, 473–491 (2016).
Rayner, N. A. et al. Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late nineteenth century. J. Geophys. Res. Atmos. 108, 4407 (2003).
Iribarne, J. V. & Godson, W. L. in Atmospheric Thermodynamics Ch. 6 (Springer, 1973).
Y.Z. thanks J. Lin and G. Vecchi for suggestions on the manuscript. Y.Z. acknowledges support under award NA18OAR4320123 from the National Oceanic and Atmospheric Administration, US Department of Commerce (the statements, findings, conclusions, and recommendations are those of the author and do not necessarily reflect the views of the National Oceanic and Atmospheric Administration or the US Department of Commerce). S.F. acknowledges support from National Science Foundation under award AGS-1733818.
The authors declare no competing interests.
Peer review information Nature Geoscience thanks the anonymous reviewers for their contribution to the peer review of this work. Primary Handling Editors: Tamara Goldin, Heike Langenberg, Tom Richardson.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
About this article
Cite this article
Zhang, Y., Held, I. & Fueglistaler, S. Projections of tropical heat stress constrained by atmospheric dynamics. Nat. Geosci. 14, 133–137 (2021). https://doi.org/10.1038/s41561-021-00695-3