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Understanding the regional pattern of projected future changes in extreme precipitation

Abstract

Changes in extreme precipitation are among the most impact-relevant consequences of climate warming1, yet regional projections remain uncertain due to natural variability2 and model deficiencies in relevant physical processes3,4. To better understand changes in extreme precipitation, they may be decomposed into contributions from atmospheric thermodynamics and dynamics5,6,7, but these are typically diagnosed with spatially aggregated data8,9 or using a statistical approach that is not valid at all locations10,11. Here we decompose the forced response of daily regional scale extreme precipitation in climate-model simulations into thermodynamic and dynamic contributions using a robust physical diagnostic8. We show that thermodynamics alone would lead to a spatially homogeneous fractional increase, which is consistent across models and dominates the sign of the change in most regions. However, the dynamic contribution modifies regional responses, amplifying increases, for instance, in the Asian monsoon region, but weakening them across the Mediterranean, South Africa and Australia. Over subtropical oceans, the dynamic contribution is strong enough to cause robust regional decreases in extreme precipitation, which may partly result from a poleward circulation shift. The dynamic contribution is key to reducing uncertainties in future projections of regional extreme precipitation.

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Figure 1: Present-day precipitation extremes and scaling.
Figure 2: Forced changes in precipitation extremes and scaling.
Figure 3: Changes in thermodynamic scaling and effects of changes in vertical winds.
Figure 4: Uncertainty of changes in full and thermodynamic scaling.

References

  1. 1

    IPCC in Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaption (eds Field, C. B. et al.) 231–290 (Cambridge Univ. Press, 2012).

  2. 2

    Fischer, E. M., Beyerle, U. & Knutti, R. Robust spatially aggregated projections of climate extremes. Nat. Clim. Change 3, 1033–1038 (2013).

    Article  Google Scholar 

  3. 3

    Wilcox, E. M. & Donner, L. J. The frequency of extreme rain events in satellite rain-rate estimates and an atmospheric general circulation model. J. Clim. 20, 53–69 (2007).

    Article  Google Scholar 

  4. 4

    Rossow, W. B., Mekonnen, A., Pearl, C. & Goncalves, W. Tropical precipitation extremes. J. Clim. 26, 1457–1466 (2013).

    Article  Google Scholar 

  5. 5

    Trenberth, K. E. Conceptual framework for changes of extremes of the hydrological cycle with climate change. Climatic Change 42, 327–339 (1999).

    Article  Google Scholar 

  6. 6

    Allen, M. R. & Ingram, W. J. Constraints on future changes in climate and the hydrological cycle. Nature 419, 224–232 (2002).

    CAS  Google Scholar 

  7. 7

    O’Gorman, P. A. Precipitation extremes under climate change. Curr. Clim. Change Rep. 1, 49–59 (2015).

    Article  Google Scholar 

  8. 8

    O’Gorman, P. A. & Schneider, T. The physical basis for increases in precipitation extremes in simulations of 21st-century climate change. Proc. Natl Acad. Sci. USA 106, 14773–14777 (2009).

    Article  Google Scholar 

  9. 9

    Sugiyama, M., Shiogama, H. & Emori, S. Precipitation extreme changes exceeding moisture content increase in MIROC and IPCC climate models. Proc. Natl Acad. Sci. USA 107, 571–575 (2010).

    CAS  Article  Google Scholar 

  10. 10

    Emori, S. & Brown, S. J. Dynamic and thermodynamic changes in mean and extreme precipitation under changed climate. Geophys. Res. Lett. 32, L17706 (2005).

    Article  Google Scholar 

  11. 11

    Chen, G., Ming, Y., Singer, N. D. & Lu, J. Testing the Clausius–Clapeyron constraint on the aerosol-induced changes in mean and extreme precipitation. Geophys. Res. Lett. 38, L04807 (2011).

    Google Scholar 

  12. 12

    Kharin, V. V., Zwiers, F. W., Zhang, X. & Wehner, M. Changes in temperature and precipitation extremes in the CMIP5 ensemble. Climatic Change 119, 345–357 (2013).

    Article  Google Scholar 

  13. 13

    Pendergrass, A. G. & Hartmann, D. L. Changes in the distribution of rain frequency and intensity in response to global warming. J. Clim. 27, 8372–8383 (2014).

    Article  Google Scholar 

  14. 14

    Westra, S., Alexander, L. V. & Zwiers, F. W. Global increasing trends in annual maximum daily precipitation. J. Clim. 26, 3904–3918 (2013).

    Article  Google Scholar 

  15. 15

    Fischer, E. M. & Knutti, R. Detection of spatially aggregated changes in temperature and precipitation extremes. Geophys. Res. Lett. 41, 547–554 (2014).

    Article  Google Scholar 

  16. 16

    Donat, M. G., Lowry, A. L., Alexander, L. V., O’Gorman, P. A. & Maher, N. More extreme precipitation in the world’s dry and wet regions. Nat. Clim. Change 6, 508–513 (2016).

    Article  Google Scholar 

  17. 17

    Fischer, E. M., Sedláček, J., Hawkins, E. & Knutti, R. Models agree on forced response pattern of precipitation and temperature extremes. Geophys. Res. Lett. 41, 8554–8562 (2014).

    Article  Google Scholar 

  18. 18

    Muller, C. J., O’Gorman, P. A. & Back, L. E. Intensification of precipitation extremes with warming in a cloud-resolving model. J. Clim. 24, 2784–2800 (2011).

    Article  Google Scholar 

  19. 19

    Singh, M. S. & O’Gorman, P. A. Influence of microphysics on the scaling of precipitation extremes with temperature. Geophys. Res. Lett. 41, 6037–6044 (2014).

    Article  Google Scholar 

  20. 20

    Vallis, G. K., Zurita-Gotor, P., Cairns, C. & Kidston, J. Response of the large-scale structure of the atmosphere to global warming. Q. J. R. Meteorol. Soc. 141, 1479–1501 (2015).

    Article  Google Scholar 

  21. 21

    He, J. & Soden, B. J. A re-examination of the projected subtropical precipitation decline. Nat. Clim. Change 7, 53–57 (2017).

    Article  Google Scholar 

  22. 22

    Pfahl, S. & Wernli, H. Quantifying the relevance of cyclones for precipitation extremes. J. Clim. 25, 6770–6780 (2012).

    Article  Google Scholar 

  23. 23

    Zappa, G., Shaffrey, L. C., Hodges, K. I., Sansom, P. G. & Stephenson, D. B. A multimodel assessment of future projections of North Atlantic and European extratropical cyclones in the CMIP5 climate models. J. Clim. 26, 5846–5862 (2013).

    Article  Google Scholar 

  24. 24

    Zappa, G., Hawcroft, M. K., Shaffrey, L., Black, E. & Brayshaw, D. J. Extratropical cyclones and the projected decline of winter Mediterranean precipitation in the CMIP5 models. Clim. Dynam. 45, 1727–1738 (2015).

    Article  Google Scholar 

  25. 25

    Lau, W. K. M. & Kim, K.-M. Robust Hadley Circulation changes and increasing global dryness due to CO2 warming from CMIP5 model projections. Proc. Natl Acad. Sci. USA 112, 3630–3653 (2015).

    CAS  Article  Google Scholar 

  26. 26

    Huang, P. Time-varying response of ENSO-induced tropical Pacific rainfall to global warming in CMIP5 models. Part I: multimodel ensemble results. J. Clim. 29, 5763–5778 (2016).

    Article  Google Scholar 

  27. 27

    Vecchi, G. A. et al. Weakening of tropical Pacific atmospheric circulation due to anthropogenic forcing. Nature 441, 73–76 (2006).

    CAS  Article  Google Scholar 

  28. 28

    Turner, A. G. & Annamalai, H. Climate change and the South Asian summer monsoon. Nat. Clim. Change 2, 587–595 (2012).

    Article  Google Scholar 

  29. 29

    O’Gorman, P. A. Sensitivity of tropical precipitation extremes to climate change. Nat. Geosci. 5, 697–700 (2012).

    Article  Google Scholar 

  30. 30

    Shepherd, T. Atmospheric circulation as a source of uncertainty in climate change projections. Nat. Geosci. 7, 703–708 (2014).

    CAS  Article  Google Scholar 

  31. 31

    Trenberth, K. E., Fasullo, J. T. & Shepherd, T. G. Attribution of climate extremes. Nat. Clim. Change 5, 725–730 (2015).

    Article  Google Scholar 

  32. 32

    Simmons, A. J., Untch, A., Jakob, C., Kallberg, P. & Undén, P. Stratospheric water vapour and tropical tropopause temperatures in ECMWF analyses and multi-year simulations. Q. J. R. Meteorol. Soc. 125, 353–386 (1999).

    Article  Google Scholar 

  33. 33

    Huffman, G. J. et al. Global precipitation at one-degree daily resolution from multi-satellite observations. J. Hydrometeorol. 2, 36–50 (2001).

    Article  Google Scholar 

  34. 34

    Xiang, B., Zhao, M., Held, I. M. & Golaz, J.-C. Predicting the severity of spurious “double ITCZ” problem in CMIP5 coupled models from AMIP simulations. Geophys. Res. Lett. 44, 1520–1527 (2017).

    Article  Google Scholar 

  35. 35

    Herold, N., Behrangi, A. & Alexander, L. S. Large uncertainties in observed daily precipitation extremes over land. J. Geophys. Res. 122, 668–681 (2017).

    Google Scholar 

  36. 36

    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).

    Article  Google Scholar 

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Acknowledgements

We acknowledge the World Climate Research Programme’s Working Group on Coupled Modelling, which is responsible for CMIP, and we thank the climate modelling groups 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. We thank NASA for providing GPCP precipitation data and ECMWF for giving access to ERA-Interim reanalysis data. P.A.O’G. acknowledges support from NSF AGS-1552195. We thank S. Fueglistaler for helpful discussions.

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S.P. initiated the study, performed the analysis based on code provided by P.A.O’G. and drafted the paper. All authors discussed the results and edited the manuscript.

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Correspondence to S. Pfahl.

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The authors declare no competing financial interests.

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Pfahl, S., O’Gorman, P. & Fischer, E. Understanding the regional pattern of projected future changes in extreme precipitation. Nature Clim Change 7, 423–427 (2017). https://doi.org/10.1038/nclimate3287

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