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Nikolaos Christidis, Richard A. Betts, and Peter A. Stott
Open access
Peter Uhe, Dann Mitchell, Paul D. Bates, Myles R. Allen, Richard A. Betts, Chris Huntingford, Andrew D. King, Benjamin M. Sanderson, and Hideo Shiogama

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.

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Jose A. Marengo, Luiz E.O.C. Aragão, Peter M. Cox, Richard Betts, Duarte Costa, Neil Kaye, Lauren T. Smith, Lincoln M. Alves, and Vera Reis
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