Contribution of sea-ice loss to Arctic amplification is regulated by Pacific Ocean decadal variability
Screen, James A.
Francis, Jennifer A.
Nature Climate Change
Nature Publishing Group
This is the author accepted manuscript. The final version is available from Nature via the DOI in this record.
Reason for embargo
The pace of Arctic warming is about double that at lower latitudes – a robust phenomenon known as Arctic amplification (AA)1. Many diverse climate processes and feedbacks cause AA2-7, including positive feedbacks associated with diminished sea ice6,7. However, the precise contribution of sea-ice loss to AA remains uncertain7,8. Through analyses of both observations and model simulations, we show that the contribution of sea-ice loss to wintertime AA appears dependent on the phase of the Pacific Decadal Oscillation (PDO). Our results suggest that for the same pattern and amount of sea-ice loss, consequent Arctic warming is larger during the negative PDO phase, relative to the positive phase, leading to larger reductions in the poleward gradient of tropospheric thickness and to more pronounced reductions in the upper-level westerlies. Given the oscillatory nature of the PDO, this relationship has the potential to increase skill in decadal-scale predictability of Arctic and sub-Arctic climate. Our results indicate that Arctic warming in response to the ongoing long-term sea-ice decline9,10 is greater (reduced) during periods of negative (positive) PDO phase. We speculate that the observed recent shift to the positive PDO phase, if maintained and all other factors being equal, could act to temporarily reduce the pace of wintertime Arctic warming in the near future.
J.A.S. was funded by a UK Natural Environment Research Council (NERC) grants NE/J019585/1 and NE/M006123/1. J.A.F. was supported by an NSF/ARCSS grant (1304097) and NASA grant (NNX14AH896). The model simulations were performed on the ARCHER UK National Supercomputing Service. We thank the NOAA ESRL and Met Office Hadley Centre for provision of observational and reanalysis data sets. We also thank D. Ackerley for helping to diagnose the cause of model crashes, C. Deser for commenting on the manuscript prior to submission, and two anonymous reviewers for constructive criticism.