The anthropogenically forced decline of Arctic sea ice is superimposed on strong internal variability. Possible drivers for this variability include fluctuations in surface albedo, clouds and water vapour, surface winds and poleward atmospheric and oceanic energy transport, but their relative contributions have not been quantified. By isolating the impact of the individual drivers in an Earth system model, we here demonstrate that internal variability of sea ice is primarily caused directly by atmospheric temperature fluctuations. The other drivers together explain only 25% of sea-ice variability. The dominating impact of atmospheric temperature fluctuations on sea ice is consistent across observations, reanalyses and simulations from global climate models. Such atmospheric temperature fluctuations occur due to variations in moist-static energy transport or local ocean heat release to the atmosphere. The fact that atmospheric temperature fluctuations are the key driver for sea-ice variability limits prospects of interannual predictions of sea ice, and suggests that observed record lows in Arctic sea-ice area are a direct response to an unusually warm atmosphere.
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Passive microwave sea-ice concentration data were obtained from http://nsidc.org/data/g02135; atmospheric temperature data from ERA-Interim and ocean temperature data from ORAS4 are available from http://www.ecmwf.int/en/forecasts/datasets/browse-reanalysis-datasets/. CMIP5 model outputs were obtained from http://esgf-node.llnl.gov/ and ftp://ftp.ceda.ac.uk/.
The MPI-ESM1.2-LR coupled climate model is distributed via http://www.mpimet.mpg.de/. The code changes to allow for non-interactive radiative feedbacks and non-radiative forcings (revision 8932) are available on request from firstname.lastname@example.org. All figures were generated using the NCAR Command Language34, available at https://doi.org/10.5065/D6WD3XH5. Plotting scripts and relevant model output used in this study are available on request from email@example.com.
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We thank M.-L. Kapsch for helpful comments on an earlier version of this manuscript. This work was funded by the Max Planck Society. Extensive computational resources were made available by the German Climate Computing Centre. We thank PCMDI for their management of CMIP5, and the various modelling groups for carrying out the simulations used here.
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