2015-10-16

Emily Lei Kang, PhD, Assistant Professor, Department of Mathematical Sciences, University of Cincinnati

"Spatial Analysis of High-Resolution Regional Climate-Change Projection over North America"

Climate models have become the primary means for scientists to project future climate change and to understand its potential impact. In this talk, temporally averaged seasonal surface-temperature fields for the current (1971-2000) and future (2041-2070) periods, produced from two regional climate models (RCMs) and driven by the same atmosphere-ocean general circulation model (GCM) in the North American Regional Climate Change Assessment Program (NARCCAP) Phase II experiment, are considered. We set up a two-way spatial analysis of variance (ANOVA) model with the factor of season, the factor of RCM, and their interaction to analyze the projected climate change, the difference between future and current temperatures. The main effects and interactions are assumed to follow the Spatial Random Effects (SRE) models; hence, the computations associated with this spatial ANOVA of high-resolution RCM outputs can be carried out without having to resort to approximations, and a flexible class of spatial covariance functions is allowed. I will also briefly discuss a number of extensions of the SRE model, including its application in data fusion and the generalization in the spatio-temporal context.

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