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

机译:北大西洋海洋表面温度的主成分分析

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The framework of principal component analysis (PCA) based on singular value decom-position (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.
机译:基于奇异值分解(SVD)的主成分分析(PCA)框架应用于北大西洋1856-2008年的每月海表温度(SST)观测。每个月SST的多年时间序列用于调查12个月以来SST变化之间的统计关系。为了获得近似的稳态条件,趋势和多年代际振荡已从数据中删除。剩余的SST残留在连续的月份之间表现出显着的相关性,这在很大程度上是由于持久性。 PCA演示了数据集的降维,并提供了一种分析描述气候系统的多元观测值的可靠方法。

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