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Rapid expansion of Greenland’s low-permeability ice slabs

Nature volume 573, pages 403–407 (2019)Cite this article

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Abstract

In recent decades, meltwater runoff has accelerated to become the dominant mechanism for mass loss in the Greenland ice sheet1,2,3. In Greenland’s high-elevation interior, porous snow and firn accumulate; these can absorb surface meltwater and inhibit runoff4, but this buffering effect is limited if enough water refreezes near the surface to restrict percolation5,6. However, the influence of refreezing on runoff from Greenland remains largely unquantified. Here we use firn cores, radar observations and regional climate models to show that recent increases in meltwater have resulted in the formation of metres-thick, low-permeability ‘ice slabs’ that have expanded the Greenland ice sheet’s total runoff area by 26 ± 3 per cent since 2001. Although runoff from the top of ice slabs has added less than one millimetre to global sea-level rise so far, this contribution will grow substantially as ice slabs expand inland in a warming climate. Runoff over ice slabs is set to contribute 7 to 33 millimetres and 17 to 74 millimetres to global sea-level rise by 2100 under moderate- and high-emissions scenarios, respectively—approximately double the estimated runoff from Greenland’s high-elevation interior, as predicted by surface mass balance models without ice slabs. Ice slabs will have an important role in enhancing surface meltwater feedback processes, fundamentally altering the ice sheet’s present and future hydrology.

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Fig. 1: Meltwater runoff over low-permeability ice slabs in southwest Greenland.
Fig. 2: Low-permeability ice slabs on the Greenland ice sheet and peripheral ice caps detected by IceBridge AR (2010–2014).
Fig. 3: Ice-slab growth and runoff computed by outputs from RCMs.

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Data and code availability

Firn cores presented in Extended Data Fig. 1 are available in the 2018 release of Greenland’s SumUp dataset32. Post-processed GPR and IceBridge AR transects, shapefiles and CSV-summaries are publicly available in Figshare project ‘Greenland Ice Slabs Data’ at https://doi.org/10.6084/m9.figshare.8309777. Codes for post-processing core, GPR, IceBridge AR and RCM data are available at https://github.com/mmacferrin/Greenland_Ice_Slabs. RCM outputs are available from the respective online data repositories for each model and/or upon request from the authors. Greenland boundary outlines used in all maps are available from the Natural Earth open-access GIS repository at https://www.naturalearthdata.com/downloads/.

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Acknowledgements

We acknowledge National Aeronautics and Space Administration (NASA) awards NNX10AR76G and NNX15AC62G for funding most of the work, including field campaigns. This work was also supported by the Retain project, funded by the Danish Council for Independent Research (grant number 4002-00234). Research leading to these results received funding from the European Research Council under the European Union’s Seventh Framework Programme (FP7/2007-2013)/ERC grant agreement 610055 as part of the ice2ice project. We thank the field team members for their contributions to field data collection in 2012–2017.

Author information

Authors and Affiliations

  1. Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, CO, USA

    M. MacFerrin, M. S. Moussavi & W. Abdalati

  2. Department of Geosciences, University of Fribourg, Fribourg, Switzerland

    H. Machguth

  3. Department of Geography, University of Zurich, Zurich, Switzerland

    H. Machguth

  4. Geological Survey of Denmark and Greenland, Copenhagen, Denmark

    D. van As & B. Vandecrux

  5. Bavarian Academy of Sciences and Humanities, Munich, Germany

    C. Charalampidis

  6. Department of Earth and Space Sciences, University of Washington, Seattle, WA, USA

    C. M. Stevens

  7. WSL Institute for Snow and Avalanche Research SLF, Davos Dorf, Switzerland

    A. Heilig

  8. Department of Earth and Environmental Sciences, Ludwig-Maximilians-University of Munich, Munich, Germany

    A. Heilig

  9. Alfred Wegener Institute Helmholtz-Centre for Polar and Marine Research, Bremerhaven, Germany

    A. Heilig

  10. Department of Civil Engineering, Technical University of Denmark, Kongens Lyngby, Denmark

    B. Vandecrux

  11. Danish Meteorological Institute, Copenhagen, Denmark

    P. L. Langen & R. Mottram

  12. Department of Geography, University of Liège, Liège, Belgium

    X. Fettweis

  13. Institute for Marine and Atmospheric Research, Utrecht University, Utrecht, The Netherlands

    M. R. van den Broeke

  14. Department of Civil Engineering, University of Colorado, Boulder, CO, USA

    W. T. Pfeffer

  15. National Snow and Ice Data Center, University of Colorado, Boulder, CO, USA

    M. S. Moussavi

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Contributions

M.MF. conceived the study question, processed the core, GPR and IceBridge AR data, post-processed the RCM output data and is the primary author of the manuscript and supplement. All authors contributed to the manuscript text, analyses, figures and revisions. M.MF., H.M., and D.v.A. planned, organized and undertook field campaigns dedicated to the data presented in this paper. C.C., C.M.S., B.V. and A.H. collected, interpreted and/or plotted field data. P.L.L., R.M., X.F. and M.R.V.d.B. provided regional climate model outputs and assisted with their results and interpretations. W.T.P. helped formulate and interpret the excess melt model. M.S.M. performed remote-sensing validation of runoff over ice slabs. W.A. supervised and oversaw the direction and formulation of the manuscript and project.

Corresponding author

Correspondence to M. MacFerrin.

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Extended data figures and tables

Extended Data Fig. 1 Firn core density profiles.

Firn density is plotted in black with ice layers indicated in blue. a, Firn cores drilled during the ACT-13 campaign5. b, A time series of firn core measurements at the KAN_U field site; data obtained in 2009–2017. c, Firn cores from the BAB_U field site, 40 km southeast of KAN_U, measured in 2015 and 2017.

Extended Data Fig. 2 Map of core locations.

IceBridge flight lines are shown in light blue and 50-m-elevation contours in grey, derived from ArcticDEM dataset31. KAN_U, at an elevation of 1,840 m, is identified on the left. IceBridge flight lines that overlap core locations are highlighted in orange.

Extended Data Fig. 3

RCM calculations of excess melt in pixels in which ice slabs are detected by IceBridge AR data.

Extended Data Fig. 4 Simulated ice slabs in Greenland drainage basins.

a, Area (×103 km2; top) and mean elevation (in metres, ±1 s.d.; bottom) of ice slabs, as detected by IceBridge AR and simulated by RCMs, around 2014. b, Ice slabs simulated using RACMO ERA-Int 2014 model results in each drainage basin.

Extended Data Table 1 Metadata of firn cores
Full size table

Supplementary information

Supplementary Information

Text and figures describing the GPR and IceBridge AR processing steps used in the main manuscript (Fig. 2).

Supplementary Table 3

List of derived empirical formula variables for the roll-correction parameters of every IceBridge AR track (Supplementary section S.2.3.2).

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MacFerrin, M., Machguth, H., As, D.v. et al. Rapid expansion of Greenland’s low-permeability ice slabs. Nature 573, 403–407 (2019). https://doi.org/10.1038/s41586-019-1550-3

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