Letter | Published:

Influence of persistent wind scour on the surface mass balance of Antarctica

Nature Geoscience volume 6, pages 367371 (2013) | Download Citation

Abstract

Accurate quantification of surface snow accumulation over Antarctica is a key constraint for estimates of the Antarctic mass balance, as well as climatic interpretations of ice-core records1,2. Over Antarctica, near-surface winds accelerate down relatively steep surface slopes, eroding and sublimating the snow. This wind scour results in numerous localized regions (≤200 km2) with reduced surface accumulation3,4,5,6,7. Estimates of Antarctic surface mass balance rely on sparse point measurements or coarse atmospheric models that do not capture these local processes, and overestimate the net mass input in wind-scour zones3. Here we combine airborne radar observations of unconformable stratigraphic layers with lidar-derived surface roughness measurements to identify extensive wind-scour zones over Dome A, in the interior of East Antarctica. The scour zones are persistent because they are controlled by bedrock topography. On the basis of our Dome A observations, we develop an empirical model to predict wind-scour zones across the Antarctic continent and find that these zones are predominantly located in East Antarctica. We estimate that 2.7–6.6% of the surface area of Antarctica has persistent negative net accumulation due to wind scour, which suggests that, across the continent, the snow mass input is overestimated by 11–36.5 Gt yr−1 in present surface-mass-balance calculations.

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References

  1. 1.

    et al. Spatial and temporal variability of snow accumulation in East Antarctica from traverse data. J. Glaciol. 51, 113–124 (2005).

  2. 2.

    , & Antarctic snow accumulation mapped using polarization of 4.3-cm wavelength microwave emission. J. Geophys. Res. 111, D06107 (2006).

  3. 3.

    et al. Extent of low-accumulation ‘wind glaze’ areas on the East Antarctic plateau: Implications for continental ice mass balance. J. Glaciol. 58, 633–647 (2012).

  4. 4.

    et al. New estimations of precipitation and surface sublimation in East Antarctica from snow accumulation measurements. Clim. Dynam. 23, 803–813 (2004).

  5. 5.

    et al. Extraordinary blowing snow transport events in East Antarctica. Clim. Dynam. 34, 1195–1206 (2010).

  6. 6.

    , & Evidence of a large surface ablation zone in central East Antarctica during the last Ice Age. Quat. Res. 59, 114–121 (2003).

  7. 7.

    et al. Accumulation variability and mass budgets of the Lambert Glacier-Amery Ice Shelf system, East Antarctica at high elevations. Ann. Glaciol. 43, 351–360 (2006).

  8. 8.

    & The surface windfield over the Antarctic ice sheets. Nature 328, 51–54 (1987).

  9. 9.

    Distribution of surface features of snow cover in Mizuho Plateau. National Institute of Polar Research. Mem. Natl Inst. Pol. Res. 7 (Special issue), 44–62 (1978-01) 1977.

  10. 10.

    , & in Proc. NIPR Symp. Polar Meteorol. Glaciol. Vol. 10, 13–24 (1996).

  11. 11.

    , , , & Spatial distribution of snow in western Dronning Maud Land, East Antarctica, mapped by a ground-based snow radar. J. Geophys. Res. 102, 20343–20353 (1997).

  12. 12.

    , , , & Spatial and temporal variability of surface mass balance near Talos Dome, East Antarctica. J. Geophys. Res. 112, F02032 (2007).

  13. 13.

    , & Snow megadunes in Antarctica: Sedimentary structures and genesis. J. Geophys. Res. 107, 4344 (2002).

  14. 14.

    , & Unconformable stratigraphy in East Antarctica: Part 1. Large firn cosets, recrystallized growth, and model evidence for intensified accumulation. J. Glaciol. 58, 240–252 (2012).

  15. 15.

    , , , & Impacts of an accumulation hiatus on the physical properties of firn at a low-accumulation polar site. J. Geophys. Res. 112, F02030 (2007).

  16. 16.

    & Spatial and temporal characterizations of hoar formation in central Greenland using SSM/I brightness temperatures. Geophys. Res. Lett. 20, 2643–2646 (1993).

  17. 17.

    et al. Widespread persistent thickening of the East Antarctic Ice Sheet by freezing from the base. Science 331, 1592–1595 (2011).

  18. 18.

    , , , & A new, high-resolution surface mass balance map of Antarctica (1979–2010) based on regional atmospheric climate modeling. Geophys. Res. Lett. 39, L04501 (2012).

  19. 19.

    et al. Modeling drifting snow in Antarctica with a regional climate model: 1. Methods and model evaluation. J. Geophys. Res. 117, D05108 (2012).

  20. 20.

    , & A new 1  km digital elevation model of the Antarctic derived from combined satellite radar and laser data—Part 1: Data and methods. The Cryosphere 3, 101–111 (2009).

  21. 21.

    , , , & Variability in accumulation rates from GPR profiling on the West Antarctic plateau. Ann. Glaciol. 39, 238–244 (2004).

  22. 22.

    , , & Satellite remote sensing of blowing snow properties over Antarctica. J. Geophys. Res. 116, D16123 (2011).

  23. 23.

    Effect of inversion winds on topographic detail and mass balance of inland icesheets. J. Glaciol. 14, 85–90 (1975).

  24. 24.

    & Accumulation in the region of Wilkes, Wilkes Land, Antarctica. J. Glaciol. 5, 3–15 (1964).

  25. 25.

    , & Blue-ice areas in Antarctica derived from NOAA AVHRR satellite data. J. Glaciol. 47, 325–334 (2001).

  26. 26.

    et al. Recent Antarctic ice mass loss from radar interferometry and regional climate modeling. Nature Geosci. 1, 106–110 (2008).

  27. 27.

    Dynamics and mass balance of four large East Antarctic outlet glaciers. Ann. Glaciol. 52, 116–126 (2011).

  28. 28.

    , , & Accelerated Antarctic ice loss from satellite gravity measurements. Nature Geosci. 2, 859–862 (2009).

  29. 29.

    , , , & Surface roughness over the northern half of Greenland Ice Sheet from airborne laser altimetry. J. Geophys. Res. 114, F01001 (2009).

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Acknowledgements

This work was supported by AGAP-NSF 0632292 (R.E.B., T.T.C., I.D., M.W.), RL-NSF 0636883 (R.E.B., I.D.), IceBridge-NASA NNNX11AC22G (R.E.B.), NSF-OPP 0538103 (T.A.S.) and NASA-NNX10AL42G (T.A.S.). We thank R. Hock, C. Shuman and R. Buck for early reviews of the paper. S. Arcone is acknowledged for helpful discussions. T. Haran, A. Block and H. Abdi are acknowledged for their help in data processing and GIS (geographic information system) support.

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Affiliations

  1. Lamont-Doherty Earth Observatory of Columbia University, Palisades, New York 10964-8000, USA

    • Indrani Das
    • , Robin E. Bell
    • , Michael Wolovick
    • , Timothy T. Creyts
    •  & Nicholas Frearson
  2. National Snow and Ice Data Center, CIRES, University of Colorado at Boulder, Colorado 80309, USA

    • Ted A. Scambos
  3. NASA Goddard Space Flight Center, Greenbelt, Maryland 20771, USA

    • Michael Studinger
  4. Polar Meteorology Group, Byrd Polar Research Center, and Atmospheric Sciences Program, The Ohio State University, Columbus, Ohio 43210, USA

    • Julien P. Nicolas
  5. Institute for Marine and Atmospheric Research Utrecht, Utrecht University, Princetonplein 5, 3584 CC Utrecht, The Netherlands

    • Jan T. M. Lenaerts
    •  & Michiel R. van den Broeke

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Contributions

I.D. processed and analysed the lidar data set, interpreted the radar data set, developed the prediction model and wrote the paper. R.E.B. oversaw the field campaign, interpreted the radar data and developed the paper. T.A.S. analysed the atmospheric parameters, provided wind-glaze data and assisted in developing the methodology and the paper. M.W. processed and analysed the radar data set and contributed to velocity modelling. T.T.C. interpreted the radar data set, assisted in methodology and developed the paper. M.S. developed the lidar system, processing software and contributed to lidar data processing. N.F. developed the radars and contributed to the processing techniques. J.P.N. helped with interpreting the atmospheric parameters and developed the paper. J.T.M.L. and M.R.v.d.B. provided the RACMO2 and blue ice data set and assisted in interpreting the results. All authors commented on the manuscript.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Indrani Das.

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DOI

https://doi.org/10.1038/ngeo1766

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