Climate Dynamics

, Volume 53, Issue 3–4, pp 1567–1580 | Cite as

A Euro-Mediterranean tree-ring reconstruction of the winter NAO index since 910 C.E.

  • Edward R. CookEmail author
  • Yochanan Kushnir
  • Jason E. Smerdon
  • A. Park Williams
  • Kevin J. Anchukaitis
  • Eugene R. Wahl


We develop a new reconstruction of the winter North Atlantic Oscillation (NAO) index using a network of 97 Euro-Mediterranean tree-ring series. The reconstruction covers the period 910–2018 C.E., making it the longest annually resolved estimate of winter NAO variability available. We use nested correlation-weighted principal components regression and the Maximum Entropy Bootstrap method to generate a 2400-member ensemble of reconstructions for estimating the final reconstruction and its quantile uncertainties. Extensive validation testing of the new reconstruction against data withheld from the calibration exercise demonstrates its skill. The skill level of the new reconstruction is also an improvement over two NAO reconstructions published earlier. Spectral analyses indicate that the new reconstruction behaves like a ‘white noise’ process with intermittent band-limited power, suggesting that the winter NAO is stochastically forced. The ‘white noise’ properties of our reconstruction are also shown to be consistent with the spectral properties of long instrumental NAO indices extending back to 1781 and NAO indices extracted from a large number of forced climate model runs covering the last millennium. In contrast, an annually resolved multi-proxy NAO reconstruction of comparable length, based in part on speleothem data, behaves more like externally forced ‘red noise’ process, which is inconsistent with our reconstruction, long observations, and forced model runs.


North Atlantic Oscillation Euro-Mediterranean tree rings Millennium reconstruction Stochastic forcing 



This research is supported by National Science Foundation Grant nos AGS-1501856, AGS-1734760, and AGS-1703029. We also acknowledge the World Climate Research Programme’s Working Group on Coupled Modelling, which is responsible for CMIP, and we thank the climate modeling groups for producing and making available their model output. The CMIP5 data used here was archived and served from the IRI/LDEO Climate Data Library. Lamont-Doherty Earth Observatory Contribution No. 8295.


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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Lamont-Doherty Earth ObservatoryPalisadesUSA
  2. 2.School of Geography and Development and Laboratory of Tree-Ring ResearchUniversity of ArizonaTucsonUSA
  3. 3.World Data Service for PaleoclimatologyNOAA National Centers for Environmental InformationBoulderUSA

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