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Towards predictive understanding of regional climate change


Regional information on climate change is urgently needed but often deemed unreliable. To achieve credible regional climate projections, it is essential to understand underlying physical processes, reduce model biases and evaluate their impact on projections, and adequately account for internal variability. In the tropics, where atmospheric internal variability is small compared with the forced change, advancing our understanding of the coupling between long-term changes in upper-ocean temperature and the atmospheric circulation will help most to narrow the uncertainty. In the extratropics, relatively large internal variability introduces substantial uncertainty, while exacerbating risks associated with extreme events. Large ensemble simulations are essential to estimate the probabilistic distribution of climate change on regional scales. Regional models inherit atmospheric circulation uncertainty from global models and do not automatically solve the problem of regional climate change. We conclude that the current priority is to understand and reduce uncertainties on scales greater than 100 km to aid assessments at finer scales.

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Figure 1: CMIP5 multimodel mean changes.
Figure 2: Effect of ocean warming pattern on precipitation change.
Figure 3: Intermodel spread of tropical precipitation change.
Figure 4: Probabilistic representation of regional climate change at a grid box near Vienna, Austria (48.5° N, 16.2° E).
Figure 5


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S.M. Long drew Figures 2 and 3. S.P.X. is supported by the National Science Foundation (NSF) and National Oceanic and Atmospheric Administration (NOAA); and M.C. by NERC NE/I022841/1. NCAR is supported by the NSF.

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S.P.X., C.D. and M.C. led the writing of the paper. All authors contributed to the development and writing of the paper.

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Correspondence to Shang-Ping Xie.

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Xie, SP., Deser, C., Vecchi, G. et al. Towards predictive understanding of regional climate change. Nature Clim Change 5, 921–930 (2015).

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