Climate Dynamics

, Volume 36, Issue 5–6, pp 945–955 | Cite as

Atmospheric inversion strength over polar oceans in winter regulated by sea ice

  • Tamlin M. PavelskyEmail author
  • Julien Boé
  • Alex Hall
  • Eric J. Fetzer


Low-level temperature inversions are a common feature of the wintertime troposphere in the Arctic and Antarctic. Inversion strength plays an important role in regulating atmospheric processes including air pollution, ozone destruction, cloud formation, and negative longwave feedback mechanisms that shape polar climate response to anthropogenic forcing. The Atmospheric Infrared Sounder (AIRS) instrument provides reliable measures of spatial patterns in mean wintertime inversion strength when compared with available radiosonde observations and reanalysis products. Here, we examine the influence of sea ice concentration on inversion strength in the Arctic and Antarctic. Correlation of inversion strength with mean annual sea ice concentration, likely a surrogate for the effective thermal conductivity of the wintertime ice pack, yields strong, linear relationships in the Arctic (r = 0.88) and Antarctic (r = 0.86). We find a substantially greater (stronger) linear relationship between sea ice concentration and surface air temperature than with temperature at 850 hPa, lending credence to the idea that sea ice controls inversion strength through modulation of surface heat fluxes. As such, declines in sea ice in either hemisphere may imply weaker mean inversions in the future. Comparison of mean inversion strength in AIRS and global climate models (GCMs) suggests that many GCMs poorly characterize mean inversion strength at high latitudes.


Temperature inversion Sea ice Arctic Antarctic AIRS 



This research was funded by the National Science Foundation under grants ARC-0714083 and ATM-0735056. Opinions, findings, or recommendations expressed here are those of the authors and do not necessarily reflect NSF views. We acknowledge the modeling groups, the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and the WCRP’s Working Group in Coupled Modeling (WGCM) for their roles in making available the WCRP CMIP3 multi-model dataset. Support for this dataset is provided by the Office of Science, U.S. Department of Energy. ECMWF ERA-40 data used in this study have been obtained from the ECMWF data server.


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Copyright information

© Springer-Verlag 2010

Authors and Affiliations

  • Tamlin M. Pavelsky
    • 1
    Email author
  • Julien Boé
    • 2
  • Alex Hall
    • 2
  • Eric J. Fetzer
    • 3
  1. 1.Department of Geological SciencesUniversity of North CarolinaChapel HillUSA
  2. 2.Department of Atmospheric and Oceanic SciencesUniversity of California Los AngelesLos AngelesUSA
  3. 3.Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadenaUSA

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