Abstract

The North Atlantic Oscillation is the dominant mode of variability of atmospheric circulation outside of the tropics in the Northern Hemisphere in winter. To understand and attribute this mode of variability is of great societal relevance for populated regions in Eurasia. It has been widely claimed that there is a robust signal of the nearly periodic 11-year solar cycle in the North Atlantic Oscillation in winter, which thereby raises the possibility of using the solar cycle to predict the circulation years in advance. Here we present evidence that contradicts this claim. First, we show the absence of a solar signal in the North Atlantic Oscillation in the instrumental record prior to the mid-1960s, and a marginally significant signal thereafter. Second, from our analysis of a global chemistry–climate model repeatedly forced with the sequence of solar irradiance since the mid-1960s, we suggest that the solar signal over this period might have been a chance occurrence due to internal variability, and hence does not imply enhanced predictability.

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Code availability

The source code of the WACCM model is part of the Community Earth System Model version 1.2.0, which is publicly distributed and can be obtained after registration at www.cesm.ucar.edu/models/cesm1.2/. All the figures were produced with Matlab, version R2017a, available at www.mathworks.com. The algorithm used to perform regression, PCA and wavelet analysis was written using built-in functions from the same Matlab distribution. More specifically, regression analysis is based on the regstats function (www.mathworks.com/help/stats/regstats.html), the wavelets on the CWT function (www.mathworks.com/help/wavelet/ref/cwt.html) and the PCA on the SVD function (www.mathworks.com/help/matlab/ref/svd.html).

Data availability

HadSLP, NOAA and 20th Century reconstructions data were provided by the NOAA/OAR/ESRL PSD from their website at www.esrl.noaa.gov/psd/. ERA20 data were provided by ECMWF from their website at www.ecmwf.int/en/forecasts/datasets/archive-datasets/reanalysis-datasets/era-20c. The SSU data are available at www.remss.com/measurements/upper-air-temperature/. The CanESM2 model data are available at http://climate-modelling.canada.ca/climatemodeldata/cgcm4/CanESM2/esmControl/index.shtml. The LENS-CAM5 model data are available through the Climate Data Gateway, hosted at NCAR and are accessible at www.earthsystemgrid.org/dataset/ucar.cgd.ccsm4.output.html. Finally, the WACCM model data are stored and available in the HPSS archive on the NCAR’s Computational and Information Systems Lab, located at www2.cisl.ucar.edu/resources/storage-and-file-systems/hpss/access.

Additional information

Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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Acknowledgements

This work is supported by a grant from the US National Science Foundation (NSF) and a cooperative agreement between NASA and Columbia University. J.O. is funded by the NSF grant DGE 1644869. All model integrations were performed at the National Center for Atmospheric Research, which is sponsored by the US NSF. The authors thank M. Sigmond and N. Gillett (Canadian Centre for Climate Modelling and Analysis) for helpful comments. We acknowledge Environment and Climate Change Canada’s Canadian Centre for Climate Modelling and Analysis for executing and making available the CanESM2 large ensemble simulations, and the Canadian Sea Ice and Snow Evolution (CanSISE) Network for proposing the simulations.

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Affiliations

  1. Department of Applied Physics and Applied Mathamatics, Columbia University, New York, NY, USA

    • Gabriel Chiodo
    • , Jessica Oehrlein
    •  & Lorenzo M. Polvani
  2. Lamont-Doherty Observatory, Columbia University, Palisades, NY, USA

    • Lorenzo M. Polvani
  3. Environment and Climate Change Canada, Victoria, British Columbia, Canada

    • John C. Fyfe
  4. National Center for Atmospheric Research, Boulder, CO, USA

    • Anne K. Smith

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Contributions

G.C. ran the climate model experiments and wrote the paper, J.O. performed the analysis of the observational and model data and G.C., J.O., L.M.P., J.C.F. and A.K.S. designed the research. All the authors helped in discussing ideas, interpreting results and writing the paper.

Competing interests

The authors declare no competing interests.

Corresponding author

Correspondence to Gabriel Chiodo.

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https://doi.org/10.1038/s41561-018-0293-3

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