Climate Dynamics

, Volume 49, Issue 9–10, pp 3011–3029 | Cite as

Timeslice experiments for understanding regional climate projections: applications to the tropical hydrological cycle and European winter circulation

  • Robin ChadwickEmail author
  • Hervé Douville
  • Christopher B. Skinner


A set of atmosphere-only timeslice experiments are described, designed to examine the processes that cause regional climate change and inter-model uncertainty in coupled climate model responses to \(CO_2\) forcing. The timeslice experiments are able to reproduce the pattern of regional climate change in the coupled models, and are applied here to two cases where inter-model uncertainty in future projections is large: the tropical hydrological cycle, and European winter circulation. In tropical forest regions, the plant physiological effect is the largest cause of hydrological cycle change in the two models that represent this process. This suggests that the CMIP5 ensemble mean may be underestimating the magnitude of water cycle change in these regions, due to the inclusion of models without the plant effect. SST pattern change is the dominant cause of precipitation and circulation change over the tropical oceans, and also appears to contribute to inter-model uncertainty in precipitation change over tropical land regions. Over Europe and the North Atlantic, uniform SST increases drive a poleward shift of the storm-track. However this does not consistently translate into an overall polewards storm-track shift, due to large circulation responses to SST pattern change, which varies across the models. Coupled model SST biases influence regional rainfall projections in regions such as the Maritime Continent, and so projections in these regions should be treated with caution.


Regional climate change Climate model uncertainty Tropical hydrological cycle European winter circulation 



We thank Sophie Tyteca for producing the CNRM-CM5 piSST simulations, and Noah Diffenbaugh and the Stanford Research Computing Center for providing computational resources and support that have contributed to these research results. We also thank Gill Martin and three anonymous reviewers for useful comments on the manuscript. Rob Chadwick was supported by the Newton Fund through the Met Office Climate Science for Service Partnership Brazil (CSSP Brazil). Chris Skinner was supported by the Turner Postdoctoral Fellowship through the University of Michigan.


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Authors and Affiliations

  1. 1.Met OfficeExeterUK

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