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• W2892550990 abstract "Our understanding of North Atlantic Ocean variability within the coupled climate system is limited by the brevity of instrumental records and a deficiency of absolutely dated marine proxies. Here we demonstrate that a spatial network of marine stable oxygen isotope series derived from molluscan sclerochronologies (δ18Oshell) can provide skillful annually resolved reconstructions of key components of North Atlantic Ocean variability with absolute dating precision. Analyses of the common δ18Oshell variability, using principal component analysis, highlight strong connections with tropical North Atlantic and subpolar gyre (SPG) sea surface temperatures and sea surface salinity in the North Atlantic Current (NAC) region. These analyses suggest that low-frequency variability is dominated by the tropical Atlantic signal while decadal variability is dominated by variability in the SPG and salinity transport in the NAC. Split calibration and verification statistics indicate that the composite series produced using the principal component analysis can provide skillful quantitative reconstructions of tropical North Atlantic and SPG sea surface temperatures and NAC sea surface salinities over the industrial period (1864–2000). The application of these techniques with extended individual δ18Oshell series provides powerful baseline records of past North Atlantic variability into the unobserved preindustrial period. Such records are essential for developing our understanding of natural climate variability in the North Atlantic Ocean and the role it plays in the wider climate system, especially on multidecadal to centennial time scales, potentially enabling reduction of uncertainties in future climate predictions." @default.
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• W2892550990 date "2018-10-01" @default.
• W2892550990 modified "2023-10-11" @default.
• W2892550990 title "Isolating and Reconstructing Key Components of North Atlantic Ocean Variability From a Sclerochronological Spatial Network" @default.
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• W2892550990 doi "https://doi.org/10.1029/2018pa003366" @default.
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