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Climate Dynamics

, Volume 20, Issue 7–8, pp 741–757 | Cite as

The impact of sea-ice dynamics on the Arctic climate system

  • S. Vavrus
  • S. P. Harrison
Article

Abstract.

Five paired global climate model experiments, one with an ice pack that only responds thermodynamically (TI) and one including sea-ice dynamics (DI), were used to investigate the sensitivity of Arctic climates to sea-ice motion. The sequence of experiments includes situations in which the Arctic was both considerably colder (Glacial Inception, ca 115,000 years ago) and considerably warmer (3 × CO2) than today. Sea-ice motion produces cooler anomalies year-round than simulations without ice dynamics, resulting in reduced Arctic warming in warm scenarios and increased Arctic cooling in cold scenarios. These changes reflect changes in atmospheric circulation patterns: the DI simulations favor outflow of Arctic air and sea ice into the North Atlantic by promoting cyclonic circulation centered over northern Eurasia, whereas the TI simulations favor southerly inflow of much warmer air from the North Atlantic by promoting cyclonic circulation centered over Greenland. The differences between the paired simulations are sufficiently large to produce different vegetation cover over >19% of the land area north of 55°N, resulting in changes in land-surface characteristics large enough to have an additional impact on climate. Comparison of the DI and TI experiments for the mid-Holocene (6000 years ago) with paleovegetation reconstructions suggests the incorporation of sea-ice dynamics yields a more realistic simulation of high-latitude climates. The spatial pattern of sea-ice anomalies in the warmer-than-modern DI experiments strongly resembles the observed Arctic Ocean sea-ice dipole structure in recent decades, consistent with the idea that greenhouse warming is already impacting the high-northern latitudes.

Keywords

Arctic Ocean Moist Static Energy Arctic Climate Surface Wind Anomaly East Greenland Coast 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgements.

This work was supported by NOAA grant NA67RJ0147, subcontracted by grant UAF-00-071 through the International Arctic Research Center at the University of Alaska-Fairbanks, and NSF grants OPP-0002239 and ATM-9905285. The authors thank Jim Maslanik and Jeremy Dunn for providing output for the modern TI simulations, Kerstin Sickel for assistance with running the BIOME4 simulations, and Pat Behling and Silvana Schott for assistance with the figures. Any opinions, findings, and conclusions expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.

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Copyright information

© Springer-Verlag 2003

Authors and Affiliations

  1. 1.Center for Climatic Research, University of Wisconsin-Madison, 1225 West Dayton Street, Madison, WI 53706, USA
  2. 2.Max Planck Institute for Biogeochemistry, P.O. Box 100164, 07701 Jena, Germany

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