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Climate

University of Wollongong

Faculty of Informatics - Papers (Archive)

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Full-Text Articles in Physical Sciences and Mathematics

Combining Outputs From The North American Regional Climate Change Assessment Program By Using A Bayesian Hierarchical Model, Emily L. Kang, Noel Cressie, Stephan R. Sain Jan 2012

Combining Outputs From The North American Regional Climate Change Assessment Program By Using A Bayesian Hierarchical Model, Emily L. Kang, Noel Cressie, Stephan R. Sain

Faculty of Informatics - Papers (Archive)

We investigate the 20-year-average boreal winter temperatures generated by an ensemble of six regional climate models (RCMs) in phase I of the North American Regional Climate Change Assessment Program. We use the long-run average (20-year integration) to smooth out variability and to capture the climate properties from the RCM outputs. We find that, although the RCMs capture the large-scale climate variation from coast to coast and from south to north similarly, their outputs can differ substantially in some regions. We propose a Bayesian hierarchical model to synthesize information from the ensemble of RCMs, and we construct a consensus climate signal …


A Spatial Analysis Of Multivariate Output From Regional Climate Models, Stephan Sain, Reinhard Furrer, Noel A. Cressie Jan 2011

A Spatial Analysis Of Multivariate Output From Regional Climate Models, Stephan Sain, Reinhard Furrer, Noel A. Cressie

Faculty of Informatics - Papers (Archive)

Climate models have become an important tool in the study of climate and climate change, and ensemble experiments consisting of multiple climate-model runs are used in studying and quantifying the uncertainty in climate-model output. However, there are often only a limited number of model runs available for a particular experiment, and one of the statistical challenges is to characterize the distribution of the model output. To that end, we have developed a multivariate hierarchical approach, at the heart of which is a new representation of a multivariate Markov random field. This approach allows for flexible modeling of the multivariate spatial …