Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

September Arctic sea-ice minimum predicted by spring melt-pond fraction

Abstract

The area of Arctic September sea ice has diminished from about 7 million km2 in the 1990s to less than 5 million km2 in five of the past seven years, with a record minimum of 3.6 million km2 in 2012 (ref. 1). The strength of this decrease is greater than expected by the scientific community, the reasons for this are not fully understood, and its simulation is an on-going challenge for existing climate models2,3. With growing Arctic marine activity there is an urgent demand for forecasting Arctic summer sea ice4. Previous attempts at seasonal forecasts of ice extent were of limited skill5,6,7,8,9. However, here we show that the Arctic sea-ice minimum can be accurately forecasted from melt-pond area in spring. We find a strong correlation between the spring pond fraction and September sea-ice extent. This is explained by a positive feedback mechanism: more ponds reduce the albedo; a lower albedo causes more melting; more melting increases pond fraction. Our results help explain the acceleration of Arctic sea-ice decrease during the past decade. The inclusion of our new melt-pond model10 promises to improve the skill of future forecast and climate models in Arctic regions and beyond.

This is a preview of subscription content, access via your institution

Access options

Rent or buy this article

Prices vary by article type

from$1.95

to$39.95

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Temporal variability of Arctic melt-pond area.
Figure 2: Spatial distribution of Arctic melt-pond area.
Figure 3: Correlation between pond and thin-ice fraction with September sea-ice extent.
Figure 4: Verification of predicted September sea-ice extent.

References

  1. Cavalieri, D., Parkinson, C., Gloersen, P. & Zwally, H. J. Sea Ice Concentrations from Nimbus-7 SMMR and DMSP SSM/I-SSMIS Passive Microwave Data. [1979–2012]. (NASA DAAC at the National Snow and Ice Data Center, 1996, updated 2013).

  2. Perovich, D. K. & Richter-Menge, J. A. Loss of sea ice in the Arctic. Ann. Rev. Mar. Sci. 1, 417–441 (2009).

    Article  Google Scholar 

  3. Stroeve, J. C. et al. Trends in Arctic sea ice extent from CMIP5, CMIP3 and observations . Geophys. Res. Lett. 39, L16502 (2012).

    Article  Google Scholar 

  4. Eicken, H. Arctic sea ice needs better forecasts. Nature 497, 431–433 (2013).

    Article  CAS  Google Scholar 

  5. Lindsay, R. W., Zhang, J., Schweiger, A. J. & Steele, M. A. Seasonal predictions of ice extent in the Arctic Ocean. J. Geophys. Res. 113, C02023 (2008).

    Article  Google Scholar 

  6. Sigmond, M., Fyfe, J. C., Flato, G. M., Kharin, V. V. & Merryfield, W. J. Seasonal forecast skill of Arctic sea ice area in a dynamical forecast system. Geophys. Res. Lett. 40, 529–534 (2013).

    Article  Google Scholar 

  7. Chevallier, M., Melia, D. S. Y., Voldoire, A., Deque, M. & Garric, G. Seasonal forecasts of the pan-Arctic sea ice extent using a GCM-based seasonal prediction system. J. Clim. 26, 6092–6104 (2013).

    Article  Google Scholar 

  8. Wang, W., Chen, M. & Kumar, A. Seasonal prediction of Arctic sea ice extent from a coupled dynamical forecast system. Mon. Weat. Rev. 141, 1375–1394 (2013).

    Article  Google Scholar 

  9. Blanchard-Wrigglesworth, E., Armour, K. C., Bitz, C. M. & DeWeaver, E. Persistence and inherent predictability of Arctic sea ice in a GCM ensemble and observations. J. Clim. 24, 231–250 (2011).

    Article  Google Scholar 

  10. Flocco, D., Schröder, D., Feltham, D. L. & Hunke, E. C. Impact of melt ponds on Arctic sea ice simulations from 1990 to 2007. J. Geophys. Res. 117, C09032 (2012).

    Article  Google Scholar 

  11. Perovich, D. K. et al. Transpolar observations of the morphological properties of Arctic sea ice-albedo. J. Geophys. Res. 114, C00A04 (2009).

    Article  Google Scholar 

  12. Hunke, E. C., Lipscomb, W. H., Turner, A. K., Jeffrey, N. & Elliot, S. CICE: The Los Alamos Sea Ice Model, Documentation and Software User’s Manual, Version 5.0. Tech. Rep. LA-CC-06-012, Los Alamos National Laboratory. Available at: http://climate.lanl.gov/Models/CICE (2013).

  13. Kanamitsu, M. et al. NCEP-DOE AMIP-II Reanalysis (R-2). Bull. Am. Meteorol. Soc. 1631–1643 (2002, updated 2013).

  14. Fetterer, F. & Untersteiner, N. Observations of melt ponds on Arctic sea ice. J. Geophys. Res. 103, 24821–24835 (1998).

    Article  Google Scholar 

  15. Eicken, H., Grenfell, T. C., Perovich, D. K., Richter-Menge, J. A. & Frey, K. Hydraulic controls of summer Arctic pack ice albedo. J. Geophys. Res. 109, C08007 (2004).

    Article  Google Scholar 

  16. Rösel, A. & Kaleschke, L. Exceptional melt pond occurrence in the years 2007 and 2011 on the Arctic sea ice revealed from MODIS satellite data. J. Geophys. Res. 117, C05018 (2012).

    Article  Google Scholar 

  17. Perovich, D. K., Nghiem, S. V., Markus, T. & Schweiger, A. Seasonal evolution and interannual variability of the local solar energy absorbed by the Arctic sea ice–ocean system. J. Geophys. Res. 112, C03005 (2007).

    Article  Google Scholar 

  18. Maslanik, J., Drobot, S., Fowler, C., Emery, W. & Barry, R. On the Arctic climate paradox and the continuing role of atmospheric circulation in affecting sea ice conditions. Geophys. Res. Lett. 34, L03711 (2007).

    Google Scholar 

  19. Parkinson, C. L. & Comiso, J. C. On the 2012 record low Arctic sea ice cover: Combined impact of preconditioning and an August storm . Geophys. Res. Lett 40, 1356–1361 (2013).

    Article  Google Scholar 

  20. Scott, F. & Feltham, D. L. A model of the three-dimensional evolution of Arctic melt ponds on first-year and multiyear sea ice. J. Geophys. Res. 115 , C12064 (2010).

    Article  Google Scholar 

  21. Overland, J., Eicken, H. & Tivy, A. http://www.arcus.org/search/seaiceoutlook/2013/june (2013).

  22. Riihelä, A., Manninen, T. & Laine, V. Observed changes in the albedo of the Arctic sea-ice zone for the period 1982–2009. Nature Clim. Change 3, 895–898 (2013).

    Article  Google Scholar 

  23. Hunke, E. C. & Dukowicz, J. K. An elastic viscous plastic model for sea ice dynamics. J. Phys. Oceanogr. 27, 1849–1868 (1997).

    Article  Google Scholar 

  24. Tsamados, M., Feltham, D. L. & Wilchinsky, A. V. Impact of a new anisotropic rheology on simulations of Arctic sea ice. J. Geophys. Res. 118, 91–107 (2013).

    Article  Google Scholar 

  25. Wilchinsky, A. & Feltham, D. Modelling the rheology of sea ice as a collection of diamond-shaped floes. J. Non-Newtonian Fluid Mech. 138, 22–32 (2006).

    Article  CAS  Google Scholar 

  26. Flocco, D. & Feltham, D. L. A continuum model of melt pond evolution on Arctic sea ice . J. Geophys. Res. 112, C08016 (2007).

    Article  Google Scholar 

  27. Flocco, D., Feltham, D. L. & Turner, A. K. Incorporation of a physically based melt pond scheme into the sea ice component of a climate model. J. Geophys. Res. 115, C08012 (2010).

    Article  Google Scholar 

  28. Ferry, N. et al. Product User Manual GLOBAL-REANALYSIS-PHYS-001-004-a and b (MyOcean, Eur. Comm., Brussels 2011).

Download references

Acknowledgements

NCEP_Reanalysis 2 data were provided by the NOAA National Weather Service, USA, from their website at http://nomads.ncep.noaa.gov/txt_descriptions/servers.shtml.

We would like to thank A. Turner and E. Hunke for their contributions to the melt-pond model and E. Hawkins for proofreading our manuscript and his advice on how to verify predictions.

Author information

Authors and Affiliations

Authors

Contributions

D.F., D.L.F. and D.S. developed the melt-pond model. M.T. and D.L.F. developed the EAP model. D.S. performed the CICE simulations and the statistical calculations. All authors discussed the results.

Corresponding author

Correspondence to David Schröder.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Supplementary information

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Schröder, D., Feltham, D., Flocco, D. et al. September Arctic sea-ice minimum predicted by spring melt-pond fraction. Nature Clim Change 4, 353–357 (2014). https://doi.org/10.1038/nclimate2203

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nclimate2203

This article is cited by

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing