A pseudoproxy evaluation of the CCA and RegEM methods for reconstructing climate fields

14 Abstract 15 Canonical correlation analysis (CCA) is evaluated for paleoclimate field reconstructions in the context 16 of pseudoproxy experiments assembled from the millennial integration (850-1999 C.E.) of the National 17 Center for Atmopsheric Research Climate System Model 1.4. A parsimonious method for selecting 18 the order of the CCA model is presented. Results suggest that the method is capable of resolving 19 approximately 3-18 climatic patterns given the estimated proxy observational network and the amount 20 of observational uncertainty. CCA reconstructions are compared to those derived from the regularized 21 expectation maximization method using ridge regression regularization (RegEM-Ridge). CCA and 22 RegEM-Ridge yield similar skill patterns that are characterized by high correlation regions collocated 23 with dense pseudoproxy sampling areas in North America and Europe. Both methods also produce 24 reconstructions characterized by spatially variable warm biases and variance losses, particularly at high 25 pseudoproxy noise levels. RegEM-Ridge in particular is subject to significantly larger variance losses 26 than CCA, even though the spatial correlation patterns of the two methods are comparable. Results 27 collectively indicate the importance of evaluating the field performance of methods that target spatial 28