Method Uncertainty Is Essential for Reliable Confidence Statements of Precipitation Projections

Peter Uhe School of Geographical Sciences, University of Bristol, Bristol, United Kingdom

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Dann Mitchell School of Geographical Sciences, University of Bristol, Bristol, United Kingdom

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Paul D. Bates School of Geographical Sciences, University of Bristol, Bristol, United Kingdom

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Myles R. Allen Environmental Change Institute, University of Oxford, Oxford, United Kingdom

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Richard A. Betts Met Office Hadley Centre, Exeter, United Kingdom
Global Systems Institute, University of Exeter, Exeter, United Kingdom

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Chris Huntingford Centre for Ecology and Hydrology, Wallingford, United Kingdom

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Andrew D. King ARC Centre of Excellence for Climate Extremes, School of Earth Sciences, University of Melbourne, Melbourne, Victoria, Australia

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Benjamin M. Sanderson European Center for Research and Advanced Training in Scientific Computing, Toulouse, France

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Hideo Shiogama National Institute for Environmental Studies, Tsukuba, Japan

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Abstract

Precipitation events cause disruption around the world and will be altered by climate change. However, different climate modeling approaches can result in different future precipitation projections. The corresponding “method uncertainty” is rarely explicitly calculated in climate impact studies and major reports but can substantially change estimated precipitation changes. A comparison across five commonly used modeling activities shows that, for changes in mean precipitation, less than half of the regions analyzed had significant changes between the present climate and 1.5°C global warming for the majority of modeling activities. This increases to just over half of the regions for changes between present climate and 2°C global warming. There is much higher confidence in changes in maximum 1-day precipitation than in mean precipitation, indicating the robust influence of thermodynamics in the climate change effect on extremes. We also find that none of the modeling activities captures the full range of estimates from the other methods in all regions. Our results serve as an uncertainty map to help interpret which regions require a multimethod approach. Our analysis highlights the risk of overreliance on any single modeling activity and the need for confidence statements in major synthesis reports to reflect this method uncertainty. Considering multiple sources of climate projections should reduce the risks of policymakers being unprepared for impacts of warmer climates relative to using single-method projections to make decisions.

Supplemental information related to this paper is available at the Journals Online website: https://doi.org/10.1175/JCLI-D-20-0289.s1.

© 2021 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Publisher’s Note: This article was revised on 20 January 2021 to include the addition of several acknowledgments in the Acknowledgments section.

Corresponding author: Peter Uhe, peter.uhe@bristol.ac.uk

Abstract

Precipitation events cause disruption around the world and will be altered by climate change. However, different climate modeling approaches can result in different future precipitation projections. The corresponding “method uncertainty” is rarely explicitly calculated in climate impact studies and major reports but can substantially change estimated precipitation changes. A comparison across five commonly used modeling activities shows that, for changes in mean precipitation, less than half of the regions analyzed had significant changes between the present climate and 1.5°C global warming for the majority of modeling activities. This increases to just over half of the regions for changes between present climate and 2°C global warming. There is much higher confidence in changes in maximum 1-day precipitation than in mean precipitation, indicating the robust influence of thermodynamics in the climate change effect on extremes. We also find that none of the modeling activities captures the full range of estimates from the other methods in all regions. Our results serve as an uncertainty map to help interpret which regions require a multimethod approach. Our analysis highlights the risk of overreliance on any single modeling activity and the need for confidence statements in major synthesis reports to reflect this method uncertainty. Considering multiple sources of climate projections should reduce the risks of policymakers being unprepared for impacts of warmer climates relative to using single-method projections to make decisions.

Supplemental information related to this paper is available at the Journals Online website: https://doi.org/10.1175/JCLI-D-20-0289.s1.

© 2021 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Publisher’s Note: This article was revised on 20 January 2021 to include the addition of several acknowledgments in the Acknowledgments section.

Corresponding author: Peter Uhe, peter.uhe@bristol.ac.uk

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