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Challenge 1: Identify and model the processes that govern climate variability and change on regional and local scales, and time-scales from months to decades; quantify and reduce the uncertainty in predictions on these scales

Following the IPCC Fourth Assessment report, the need for more detailed and reliable information about expected changes in climate, and climate impacts, at regional and local scales, is widely recognised. This information is needed by governments, who are responsible for formulating policies on mitigation and adaptation, and by a much wider range of organisations that are responsible for planning climate sensitive activities and investments. Current predictions of regional-to-local scale climate change are subject to very large uncertainty, which limits their usefulness for planning and policy purposes. This uncertainty reflects weaknesses in the models that are used to generate predictions and, more fundamentally, weaknesses in our understanding of the processes that govern climate variability and change on these scales. There is an urgent need for research to advance process understanding, and to improve climate models and prediction systems. Important new opportunities are associated with the availability of new observational datasets, the exploitation of new modelling tools (e.g. higher resolution regional and global models), and the development of new strategies for testing models against observations.


  • Improve understanding and model representation of the atmospheric and other processes that govern climate on regional and local space scales, and time-scales up to decades, including natural variability and the response to anthropogenic forcing by greenhouse gases, aerosols and other factors.
  • Identify and quantify the emerging signal of anthropogenic climate change on global, regional and local scales, and use observations with models to constrain predictions of future climate.
  • Exploit existing and new observations, and new strategies, to test climate models at a process level.
  • Develop capability for initialised climate predictions.
  • Advance capability to predict decadal changes in high impact weather.
  • Work with partners to determine the impacts of climate change on regional and local scales, and to address science questions relevant to climate adaptation policy.