Statistical Methods for Climate Model Ensembles

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Climate models are complex computer programs that simulate the physical and chemical processes in the atmosphere and oceans. These are used to obtain projections of temperature and other meteorological variables given changes in forcings such as changes in atmospheric greenhouse gases. These simulations allow us to quantify the influence of human activity on the earth system. Since different climate models are better at capturing different aspects of the complex climate processes, it has become standard practice to produce ensembles of climate projections using multiple climate models. How best to combine these climate models to produce a single probabilistic projection has become an important research question. This interdisciplinary project will develop new statistical tools to analyse complex data coming from climate research. The expected outcome will be the development of statistical theory and methodology, including spatial temporal, extremes, and robust quantile methods, for ensemble data.

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Supervisory team

Mathematics and Statistics

mathematics and statistics

Climate Change Research Centre

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