PRINCIPAL COMPONENT ANALYSIS OF SEA SURFACE TEMPERATURE IN THE NORTH ATLANTIC OCEAN

被引:3
作者
Andronache, Constantin [1 ]
机构
[1] Boston Coll, Chestnut Hill, MA 02467 USA
来源
INTERNATIONAL JOURNAL OF MODERN PHYSICS C | 2009年 / 20卷 / 11期
基金
美国海洋和大气管理局;
关键词
Principal component analysis; correlation matrix; eigenvalues; singular value decomposition; CLIMATE VARIABILITY; SST ANOMALIES; OSCILLATION; PERSISTENCE; PACEMAKER; CENTURIES; RAINFALL;
D O I
10.1142/S0129183109014734
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
The framework of principal component analysis (PCA) based on singular value decomposition (SVD) is applied to the monthly sea surface temperature (SST) observations in the North Atlantic Ocean for the time interval 1856-2008. Multiyear time series of SST for each month are used to investigate the statistical relationship between SST variations from the 12 months. To obtain approximate stationary conditions, the trend and a multidecadal oscillation are removed from the data. The remaining SST residuals exhibit remarkable correlation between successive months, due largely to persistence. PCA demonstrates the dimension reduction of the data sets and provides a robust way of analyzing multivariate observations describing the climate system.
引用
收藏
页码:1789 / 1802
页数:14
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