Reconstructing North Atlantic marine climate variability using an absolutely-dated sclerochronological network

• Published in: Palaeogeography, Palaeoclimatology, Palaeoecology
• Main Authors: Reynolds, DJ, Richardson, CA, Scourse, JD, Butler, PG, Hollyman, P, Román-González, A, Hall, IR
• Format: Article in Journal/Newspaper
• Language: English
• Published: Elsevier 2016
• Subjects: Sclerochronology; Spatial network; Arctica islandica; Glycymeris glycymeris; North Atlantic; North Atlantic oscillation; Northeast Atlantic
• Online Access: http://hdl.handle.net/10871/26357; https://doi.org/10.1016/j.palaeo.2016.08.006

This is the final version of the article. Available from Elsevier via the DOI in this record. Reconstructing regional to hemispheric-scale climate variability requires the application of spatially representative and climatically sensitive proxy archives. Large spatial networks of dendrochronologies have facilitated the reconstruction of atmospheric variability and inferred variability in the Atlantic Ocean system. However, the marine environment has hitherto lacked the direct application of the spatial network approach because of the small number of individual absolutely-dated marine archives. In this study we present the first analyses of a network of absolutely-dated annually-resolved growth increment width chronologies from the marine bivalves Glycymeris glycymeris and Arctica islandica. The network contains eight chronologies spanning > 500 km along the western British continental shelf from the southern Irish Sea to North West Scotland. Correlation analysis of the individual chronologies and a suite of climate indices, including the Atlantic Multidecadal Oscillation (AMO), Central England surface air temperature (CET), northeast Atlantic sea surface temperatures (SST's) and the winter North Atlantic Oscillation (wNAO), demonstrates that, despite the large geographical distances been sites and the heterogeneous nature of the marine environment, the increment width variability in these series contains an element of coherence likely driven by a common response to changing environmental forcing. A nested Principal component analysis (PCA) was used to construct five composite series which explain between 31% and 74% of the variance across the individual chronologies. Linear regression analyses indicate that the composite series explain up to 41% of the variance in Northeast Atlantic SSTs over the calibration period (1975–2000). Calibration verification (reduction of error [RE] and coefficient of efficiency [CE]) statistics indicate that the composite series contains significant skill at reconstructing ...