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Principal components analysis (PCA) and singular value decomposition (SVD) are used to identify the primary modes of decadal and multidecadal variability in annual global Palmer Drought Severity Index (PDSI) values and sea-surface temperatures (SSTs). The PDSI and SST data for 1925–2003 were detrended and smoothed (with a 10-year moving average) to isolate the decadal and multidecadal variability. The first two principal components (PCs) of the PDSI PCA explained almost 38% of the decadal and multidecadal variance in the detrended and smoothed global annual PDSI data. The first two PCs of detrended and smoothed global annual SSTs explained nearly 56% of the decadal variability in global SSTs. The PDSI PCs and the...
Categories: Publication; Types: Citation; Tags: PDSI, SST, decadal variability, drought