Keeping global warming within 1.5 °C constrains emergence of aridification

Abstract

Aridity—the ratio of atmospheric water supply (precipitation; P) to demand (potential evapotranspiration; PET)—is projected to decrease (that is, areas will become drier) as a consequence of anthropogenic climate change, exacerbating land degradation and desertification1,2,3,4,5,6. However, the timing of significant aridification relative to natural variability—defined here as the time of emergence for aridification (ToEA)—is unknown, despite its importance in designing and implementing mitigation policies7,8,9,10. Here we estimate ToEA from projections of 27 global climate models (GCMs) under representative concentration pathways (RCPs) RCP4.5 and RCP8.5, and in doing so, identify where emergence occurs before global mean warming reaches 1.5 °C and 2 °C above the pre-industrial level. On the basis of the ensemble median ToEA for each grid cell, aridification emerges over 32% (RCP4.5) and 24% (RCP8.5) of the total land surface before the ensemble median of global mean temperature change reaches 2 °C in each scenario. Moreover, ToEA is avoided in about two-thirds of the above regions if the maximum global warming level is limited to 1.5 °C. Early action for accomplishing the 1.5 °C temperature goal can therefore markedly reduce the likelihood that large regions will face substantial aridification and related impacts.

Access optionsAccess options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Fig. 1: Spatial distributions of the aridity index and related climate regime in present climate, and regime changes if the aridity index decreases by 0.5N.
Fig. 2: Spatial distributions of multi-model ensemble median year of ToEA and the 16–84% range.
Fig. 3: Spatial distributions of regions with ToEA ≤ t 1.5 and t 1.5 < ToEA ≤ t 2, and proportions of GCM simulations that show t 1.5, t 2 and ToEA in each particular year.
Fig. 4: Total area and present-day population count over regions with ToEA ≤ t 1.5 and ToEA ≤ t 2 under the RCP4.5 and RCP8.5 scenarios.

References

  1. 1.

    Collins, M. et al. Climate Change 2013: The Physical Science Basis (eds Stocker, T. F. et al.) (IPCC, Cambridge Univ. Press, Cambridge, UK, 2013).

  2. 2.

    Huang, J., Yu, H., Guan, X., Wang, G. & Guo, R. Accelerated dryland expansion underclimate change. Nat. Clim. Change 6, 166–171 (2016).

  3. 3.

    Feng, S. & Fu, Q. Expansion of global drylands under a warming climate. Atmos. Chem. Phys. 13, 10081–10094 (2013).

  4. 4.

    Sherwood, S. & Fu, Q. A drier future? Science 343, 737–739 (2014).

  5. 5.

    Lin, L., Gettelman, A., Fu, Q. & Xu, Y. Simulated differences in 21st century aridity due to different scenarios of greenhouse gases and aerosols. Climatic Change https://doi.org/10.1007/s10584-016-1615-3 (2016).

  6. 6.

    Fu, Q., Lin, L., Huang, J., Feng, S. & Gettelman, A. Changes in terrestrial aridity for the period 850–2080 from the Community Earth System Model. J. Geophys. Res. Atmos. 121, 2857–2873 (2016).

  7. 7.

    Mahlstein, I., Knutti, R., Solomon, S. & Portmann, R. W. Early onset of significant local warming in low latitude countries. Environ. Res. Lett. 6, 034009 (2011).

  8. 8.

    Hawkins, E. & Sutton, R. The potential to narrow uncertainty in projections of regional precipitation change. Clim. Dyn. 37, 407–418 (2011).

  9. 9.

    Hawkins, E. & Sutton, R. Time of emergence of climate signals. Geophys. Res. Lett. 39, L01702 (2012).

  10. 10.

    King, A. D. et al. The timing of anthropogenic emergence in simulated climate extremes. Environ. Res. Lett. 10, 094015 (2015).

  11. 11.

    Middleton, N. et al. World Atlas of Desertification. 2nd edn (Arnold, London, 1997).

  12. 12.

    Mosley, L. M. Drought impacts on the water quality of freshwater systems; review and integration. Earth Sci. Rev. 140, 203–214 (2015).

  13. 13.

    Westerling, A. L., Hidalgo, H. G., Cayan, D. R. & Swetnam, T. W. Warming and earlier spring increase western US forest wildfire activity. Science 313, 940–943 (2006).

  14. 14.

    Novick, K. A. et al. The increasing importance of atmospheric demand for ecosystem water and carbon fluxes. Nat. Clim. Change 6, 1023–1027 (2016).

  15. 15.

    Webber, H. et al. Uncertainty in future irrigation water demand and risk of crop failure for maize in Europe. Environ. Res. Lett. 11, 074007 (2016).

  16. 16.

    Huang, J., Yu, H., Dai, A., Wei, Y. & Kang, L. Drylands face potential threat under 2 °C global warming target. Nat. Clim. Change 7, 417–422 (2017).

  17. 17.

    Sedláček, J. & Knutti, R. Half of the world’s population experience robust changes in the water cycle for a 2 °C warmer world. Environ. Res. Lett. 9, 044008 (2014).

  18. 18.

    Dai, A. Increasing drought under global warming in observations and models. Nat. Clim. Change 3, 52–58 (2012).

  19. 19.

    Gonzalez, P., Neilson, R. P., Lenihan, J. M. & Drapek, R. J. Global patterns in the vulnerability of ecosystems to vegetation shifts due to climate change. Glob. Ecol. Biogeogr. 19, 755–768 (2010).

  20. 20.

    D’Odorico, P., Bhattachan, A., Davis, K. F., Ravi, S. & Runyan, C. W. Global desertification: drivers and feedbacks. Adv. Water Resour. 51, 326–344 (2013).

  21. 21.

    Vicente-Serrano, S. M. et al. Evidence of increasing drought severity caused by temperature rise in southern Europe. Environ. Res. Lett. 9, 044001 (2014).

  22. 22.

    Joshi, M., Hawkins, E., Sutton, R., Lowe, J. & Frame, D. Projections of when temperature change will exceed 2 °C above pre-industrial levels. Nat. Clim. Change 1, 407–412 (2011).

  23. 23.

    Park, C.-E., Jeong, S.-J., Ho, C.-H. & Kim, J. Regional variations in potential plant habitat changes in response to multiple global warming scenarios. J. Clim. 28, 2884–2899 (2015).

  24. 24.

    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).

  25. 25.

    Barbeta, A. et al. The combined effects of a long-term experimental drought and an extreme drought on the use of plant-water sources in a Mediterranean forest. Glob. Change Biol. 21, 1213–1225 (2015).

  26. 26.

    Schleussner, C.-F. et al. Science and policy characteristics of the Paris Agreement temperature goal. Nat. Clim. Change 6, 827–835 (2016).

  27. 27.

    Hawkins, E. et al. Estimating changes in global temperature since the preindustrial period. Bull. Am. Meteorol. Soc. 98, 1841–1856 (2017).

  28. 28.

    Caesar, J. et al. Response of the HadGEM2 earth system model to future greenhouse gas emissions pathways to the year 2300. J. Clim. 26, 3275–3284 (2013).

  29. 29.

    Milly, P. C. D. & Dunne, K. A. Potential evapotranspiration and continental drying. Nat. Clim. Change 6, 946–949 (2016).

  30. 30.

    Rogelj, J. et al. Paris Agreement climate proposals need a boost to keep warming well below 2 °C. Nature 534, 631–639 (2016).

  31. 31.

    Chen, M., Xie, P., Janowiak, J. E. & Arkin, P. A. Global land precipitation: a 50-yr monthly analysis based on gauge observations. J. Hydrometeorol. 3, 249–266 (2002).

  32. 32.

    Fan, Y. & van den Dool, H. A global monthly land surface air temperature analysis for 1948–present. J. Geophys. Res. 113, D01103 (2008).

  33. 33.

    Allen, R. G. Pereira, L. S., Raes, D. & Smith, M. Crop Evapotranspiration–Guidelines for Computing Crop Water Requirements. FAO Irrigation and Drainage Paper 56 (FAO, 1998).

  34. 34.

    Mastrandrea, M. D. et al. Guidance Note for Lead Authors of the IPCC Fifth Assessment Report on Consistent Treatment of Uncertainties (Intergovernmental Panel on Climate Change, 2010).

  35. 35.

    Murakami, D. & Yamagata, Y. Estimation of gridded population and GDP scenarios with spatially explicit statistical downscaling. Preprint at https://arxiv.org/abs/1610.09041 (2016).

Download references

Acknowledgements

S.-J.J. and C.-E.P. were supported by the startup funding of the Southern University of Science and Technology (SUSTECH). J.L. was supported by the National Science Fund for Distinguished Youth Scholars (41625001). J.L. was supported by part of the research funding provided by the Southern University of Science and Technology (grant no. G01296001). T.O. was supported by the Belmont Forum/JPI-Climate project INTEGRATE (NERC NE/P006809/1). M.J. was supported by the UK Natural Environment Research Council Grant Robust Spatial Projections (NE/N018397/1). C.-H.H. and H.P. were funded by the Korea Ministry of Environment as part of the ‘Climate Change Correspondence Program’. B.-M.K. was supported by Korea Polar Research Institute Project (PE17130). We acknowledge the World Climate Research Program’s Working Group on Coupled Modelling, which is responsible for CMIP, and we thank the climate modeling groups (listed in Supplementary Table 1 of this paper) for producing and making available their model output. For CMIP the US Department of Energy’s Program for Climate Model Diagnosis and Intercomparison provides coordinating support and led development of software infrastructure in partnership with the Global Organization for Earth System Science Portals.

Author information

C.-E.P. and S.-J.J. conceived and designed the study, analysed data and wrote the paper. M.J. and T.J.O. improved the study, provided data and wrote the paper. C.-H.H., S.P., D.C., J.L., H.Y., H.P., B.-M.K. wrote the paper. S.F. provided data and wrote the paper.

Correspondence to Su-Jong Jeong.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Additional information

Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Supplementary Information

Model Validation, Supplementary References, Supplementary Table 1 and Supplementary Figures 1–9

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Further reading