Abstract
The principal components derived by Wallace and Gutzler (1981) from a 500 mb height data set are linearly transformed using the varimax method. Their data set consists of 45 winter months of National Meteorological Center analyses of Northern Hemisphere 500 mb height. The linear transformation (or rotation) of the principal components emphasizes the strongest relationships within the 500 mb height data set; hence, spatial patterns associated with the rotated principal components are simpler to interpret than the spatial patterns associated with the unrotated components. The teleconnection patterns identified by Wallace and Gutzler (1981) on the basis of the negative extrema approach closely resemble several of the spatial patterns of the rotated principal components. In order to show the seasonal dependence of the rotated principal components, an expanded data set consisting of 30 years of 500 mb height data is used. Most of the teleconnection patterns derived from the 90 winter month data set ar... Abstract The principal components derived by Wallace and Gutzler (1981) from a 500 mb height data set are linearly transformed using the varimax method. Their data set consists of 45 winter months of National Meteorological Center analyses of Northern Hemisphere 500 mb height. The linear transformation (or rotation) of the principal components emphasizes the strongest relationships within the 500 mb height data set; hence, spatial patterns associated with the rotated principal components are simpler to interpret than the spatial patterns associated with the unrotated components. The teleconnection patterns identified by Wallace and Gutzler (1981) on the basis of the negative extrema approach closely resemble several of the spatial patterns of the rotated principal components. In order to show the seasonal dependence of the rotated principal components, an expanded data set consisting of 30 years of 500 mb height data is used. Most of the teleconnection patterns derived from the 90 winter month data set ar...