Northern Hemispheric teleconnection indices, created by rotated principle component analysis (RPCA), and the Standardized Southern Oscillation Index are statistically compared to the Heating Degree Days (HDDs) and Cooling Degree Days (CDDs) of 14 U.S. locations. HDDs and CDDs were summed over three month periods for a seasonal summation. Teleconnection indices found to be leading modes, using RPCA, in a particular month were compared to the HDD/CDD summation of the following three months in order to create a predictive model.
First, a comparison of simple linear regression was accomplished and results showed numerous valid models, but the amount of data resolved by the models was rarely over 30%. The HDDs and CDDs where then categorized and analyzed with a classification tree, data mining program, however, the results proved difficult to extract any predictive quantitative information.
Finally a CART analysis was performed on the uncategorized HDDs/CDDs and regression tree analysis showed an excellent conditional predictive outcome. At each conditional outcome a range is produced using the predicted standard deviations about the mean. When teleconnection indices were put into the conditional model, 95% of the time the resulting HDDs/CDDs fell into the calculated range. This conditional model was verified using an independent data set withheld from the original analysis.