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Understanding the regional pattern of projected future changes in extreme precipitation

Nature Climate Change volume 7, pages 423–427 (2017)Cite this article

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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.

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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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Authors and Affiliations

  1. Institute for Atmospheric and Climate Science, ETH Zurich, 8092 Zurich, Switzerland

    S. Pfahl & E. M. Fischer

  2. Department of Earth, Atmospheric and Planetary Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA

    P. A. O’Gorman

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  1. S. Pfahl
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Contributions

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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