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Isolating and reconstructing key components of North Atlantic Ocean variability from a sclerochronological spatial network

Reynolds, David J., Hall, Ian R., Slater, Sophie, Mette, M., Wanamaker, A. D., Scourse, J. D., Garry, F. K. and Halloran, P. R. 2018. Isolating and reconstructing key components of North Atlantic Ocean variability from a sclerochronological spatial network. Paleoceanography and Paleoclimatology 33 (10) , pp. 1086-1098. 10.1029/2018PA003366
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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 analyses (PCA), highlight strong connections with tropical North Atlantic and subpolar gyre (SPG) sea surface temperatures (SSTs) and sea surface salinity (SSS) in the North Atlantic Current (NAC) region. These analyses suggest that low frequency variability is dominated by the tropical Atlantic signal whilst 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 PCA can provide skillful quantitative reconstructions of tropical North Atlantic and SPG SSTs and NAC SSSs over the industrial period (1864‐2000). The application of these techniques with extended individual δ18Oshell series provide powerful baseline records of past North Atlantic variability into the unobserved pre‐industrial 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 multi‐decadal to centennial timescales, potentially enabling reduction of uncertainties in future climate predictions.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Earth and Ocean Sciences
Publisher: Wiley
ISSN: 2572-4517
Funders: NERC
Date of First Compliant Deposit: 4 October 2018
Date of Acceptance: 26 September 2018
Last Modified: 08 May 2019 02:42
URI: http://orca.cf.ac.uk/id/eprint/115495

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