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Decoupling of the Arctic Oscillation and North Atlantic Oscillation in a warmer climate


The North Atlantic Oscillation and the Arctic Oscillation are modes of climate variability affecting temperature and precipitation in the mid-latitudes. Here we use reanalysis data and climate model simulations of historical and warm climates to show that the relationship between the two oscillations changes with climate warming. The two modes are currently highly correlated, as both are strongly influenced by the downward propagation of stratospheric polar vortex anomalies into the troposphere. When considering a very warm climate scenario, the hemispherically defined Arctic Oscillation pattern shifts to reflect variability of the North Pacific storm track, while the regionally defined North Atlantic Oscillation pattern remains stable. The stratosphere remains an important precursor for North Atlantic Oscillation, and surface Eurasian and Aleutian pressure anomalies precede stratospheric anomalies. Idealized general circulation model simulations suggest that these modifications are linked to the stronger warming of the Pacific compared with the slower warming of the Atlantic Ocean.

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Fig. 1: SLP climatology and modes of variability.
Fig. 2: Spatial and temporal correlations.
Fig. 3: Stratosphere–troposphere coupling: weak polar vortex.
Fig. 4: Climatology response and natural variability.

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Data availability

All CMIP5 data used in this study are available on Earth System Grid Federation (ESGF) on the following link: NOAA-CFSR reanalysis data are available at ERA-Interim reanalysis data are available at

Code availability

The ICTP AGCM ‘SPEEDY model’ can be downloaded by contacting F. Kucharski ( or as indicated in the following link: Codes used to set up model simulations, analyse data and create figures can be provided upon request from the corresponding author.


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We acknowledge the World Climate Research Programme’s Working Group on Coupled Modelling, which is responsible for the Coupled Model Intercomparison Project (CMIP), and thank the climate modelling groups (listed in Data availability) for producing and making available their model output. M.E.H. and C.P. gratefully acknowledge hospitality from the Department of Earth and Planetary Sciences, Harvard University, during part of this work. M.E.H was supported by Cariplo Foundation, EXTRA project and HPC-TRES grant no. 2017-03. This article is an outcome of Progetto Dipartimenti di Eccellenza, funded by MIUR. We acknowledge CINECA HPC grant no. IsC65_CSIPAR and FAQC UniMiB grant. M.E.H. would like to thank F. Kucharski for providing SPEEDY model and for the insightful discussions. E.T. was supported by the NSF Climate Dynamics programme grant no. AGS-1924538, and thanks the Weizmann Institute of Science for its hospitality during parts of this work.

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Authors and Affiliations



M.E.H. conducted the simulations and analysed the data. The three authors equally contributed to conceiving and designing the study, interpreting the results and writing the manuscript.

Corresponding author

Correspondence to Mostafa E. Hamouda.

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Peer review information Nature Climate Change thanks Edwin Gerber and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 The Arctic Oscillation in ERA-Interim reanalysis, historical and RCP8.5.

The leading EOF mode (AO) for wintertime (DJF) sea-level pressure (SLP) for Historical (Hist) and RCP8.5 in CMIP5 models. Note that SPEEDY panels refer to the control run using climatology (CTL) and for Pacific SST perturbation run (Pac_P). (Unit: hPa corresponding to 1 standard deviation of the PC). Explained variance by the EOF is indicated on top.

Extended Data Fig. 2 Pacific ocean SST response is stronger than the Atlantic.

Climatology response of DJF sea surface temperature (RCP8.5-Historical) from MPI-ESM-LR.

Extended Data Fig. 3 SPEEDY General Circulation Model set up.

SPEEDY SST forcing design for Pac_P run: Positive Gaussian SST in the North Pacific Ocean with a peak of 6°C.

Extended Data Fig. 4 Strong Polar Vortex.

a, Same as fig. 3 except that it is for the strong polar vortex (SPV). The condition for a SPV event is when the 10 hPa NAM index is ≥ + 1. Stippling shows the 95% statistically significant anomalies using boot-strapping approach.

Extended Data Fig. 5 Weak polar vortex in IPSL-CM5A-LR.

a, Same as Fig. 3 & extended data Fig. 4, except that it is for IPSL-CM5A-LR.

Extended Data Fig. 6 Weak polar vortex in SPEEDY AGCM experiment.

a, Same as fig. 3, except that it is for SPEEDY AGCM. Note that the condition for the onset is based on NAM index at 30 hPa.

Extended Data Fig. 7 Polar vortex influence in the Atlantic sector.

Same as in fig. 3, except that here NAM index is for NAO domain instead of AO domain. The condition for the onset is still when the 10 hPa NAM index is ≤ − 1.5 for weak polar vortex. a, CFSR reanalysis. b, MPI historical. c, MPI RCP8.5. Stippling indicates the 95% statistically significant anomalies using boot-strapping approach.

Extended Data Fig. 8 Polar vortex influence in the Atlantic sector.

Same as in extended data Fig. 7, except for IPSL-CM5A-LR model.

Extended Data Fig. 9 Eurasian high and Aleutian low-pressure centres leading weak polar vortex.

Same as in fig. 4a, except for IPSL-CM5A-LR. (corresponds to the upward propagating surface anomalies in extended data fig. 5b).

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Hamouda, M.E., Pasquero, C. & Tziperman, E. Decoupling of the Arctic Oscillation and North Atlantic Oscillation in a warmer climate. Nat. Clim. Chang. 11, 137–142 (2021).

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