A Rotated Principal Component Analysis of the Interannual Variability of the Northern Hemisphere 500 mb Height FieldSource: Monthly Weather Review:;1981:;volume( 109 ):;issue: 010::page 2080Author:Horel, John D.
DOI: 10.1175/1520-0493(1981)109<2080:ARPCAO>2.0.CO;2Publisher: American Meteorological Society
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 are ?seesaws? with the southernmost center of high correlation located in the subtropics. In some cases, additional centers of high correlation are located downstream of the two primary centers. The spatial patterns associated with the rotated principal components based on 90 summertime months are analogous to those for the wintertime months but are displaced northward along with the displacement of the time mean jet streams and storm-track regions.
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contributor author | Horel, John D. | |
date accessioned | 2017-06-09T16:03:35Z | |
date available | 2017-06-09T16:03:35Z | |
date copyright | 1981/10/01 | |
date issued | 1981 | |
identifier issn | 0027-0644 | |
identifier other | ams-59963.pdf | |
identifier uri | http://onlinelibrary.yabesh.ir/handle/yetl/4200579 | |
description 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 are ?seesaws? with the southernmost center of high correlation located in the subtropics. In some cases, additional centers of high correlation are located downstream of the two primary centers. The spatial patterns associated with the rotated principal components based on 90 summertime months are analogous to those for the wintertime months but are displaced northward along with the displacement of the time mean jet streams and storm-track regions. | |
publisher | American Meteorological Society | |
title | A Rotated Principal Component Analysis of the Interannual Variability of the Northern Hemisphere 500 mb Height Field | |
type | Journal Paper | |
journal volume | 109 | |
journal issue | 10 | |
journal title | Monthly Weather Review | |
identifier doi | 10.1175/1520-0493(1981)109<2080:ARPCAO>2.0.CO;2 | |
journal fristpage | 2080 | |
journal lastpage | 2092 | |
tree | Monthly Weather Review:;1981:;volume( 109 ):;issue: 010 | |
contenttype | Fulltext |