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Granular decoherence precedes ice mélange failure and glacier calving at Jakobshavn Isbræ

Nature Geoscience volume 14, pages 417–422 (2021)Cite this article

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Abstract

The stability of the world’s largest glaciers and ice sheets depends on mechanical and thermodynamic processes occurring at the glacier–ocean boundary. A buoyant agglomeration of icebergs and sea ice, referred to as ice mélange, often forms along this boundary and has been postulated to affect ice-sheet mass losses by inhibiting iceberg calving. Here, we use terrestrial radar data sampled every 3 min to show that calving events at Jakobshavn Isbræ, Greenland, are preceded by a loss of flow coherence in the proglacial ice mélange by up to an hour, wherein individual icebergs flowing in unison undergo random displacements. A particle dynamics model indicates that these fluctuations are likely due to buckling and rearrangements of the quasi-two-dimensional material. Our results directly implicate ice mélange as a mechanical inhibitor of iceberg calving and further demonstrate the potential for real-time detection of failure in other geophysical granular materials.

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Fig. 1: Jakobshavn Isbræ and proglacial ice mélange.
Fig. 2: TRI-derived 2D velocity data products.
Fig. 3: Variations in speed and bulk strain rate over time.
Fig. 4: Particle dynamics model.

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Data availability

The TRI-derived 2D velocity dataset generated and analysed during the current study will be available at the National Snow and Ice Data Center (https://nsidc.org; https://doi.org/10.5067/FKPL8IY02XWS).

References

  1. Amundson, J. M. et al. Ice mélange dynamics and implications for terminus stability, Jakobshavn Isbræ, Greenland. J. Geophys. Res. Earth Surf. 115, F01005 (2010).

    Article  Google Scholar 

  2. Enderlin, E. M., Hamilton, G. S., Straneo, F. & Sutherland, D. A. Iceberg meltwater fluxes dominate the freshwater budget in Greenland’s iceberg-congested glacial fjords. Geophys. Res. Lett. 43, 11287–11294 (2016).

    Article  Google Scholar 

  3. Moon, T. et al. Subsurface iceberg melt key to Greenland fjord freshwater budget. Nat. Geosci. 11, 49–54 (2018).

    Article  Google Scholar 

  4. Martin, T., Tsamados, M., Schroeder, D. & Feltham, D. L. The impact of variable sea ice roughness on changes in Arctic Ocean surface stress: a model study. J. Geophys. Res. Oceans 121, 1931–1952 (2016).

    Article  Google Scholar 

  5. Hewitt, I. J. Subglacial plumes. Annu. Rev. Fluid Mech. 52, 145–169 (2020).

    Article  Google Scholar 

  6. Davison, B. J., Cowton, T. R., Cottier, F. R. & Sole, A. J. Iceberg melting substantially modifies oceanic heat flux towards a major Greenlandic tidewater glacier. Nat. Commun. 11, 5983 (2020).

    Article  Google Scholar 

  7. Cassotto, R., Fahnestock, M., Amundson, J. M., Truffer, M. & Joughin, I. Seasonal and interannual variations in ice mélange and its impact on terminus stability, Jakobshavn Isbræ, Greenland. J. Glaciol. 61, 76–88 (2015).

    Article  Google Scholar 

  8. Joughin, I., Shean, D. E., Smith, B. E. & Floricioiu, D. A decade of variability on Jakobshavn Isbræ: ocean temperatures pace speed through influence on mélange rigidity. Cryosphere 14, 211–227 (2020).

    Article  Google Scholar 

  9. Ekstrom, G., Nettles, M. & Abers, G. A. Glacial earthquakes. Science 302, 622–624 (2003).

    Article  Google Scholar 

  10. Amundson, J. M. et al. Glacier, fjord and seismic response to recent large calving events, Jakobshavn Isbræ, Greenland. Geophys. Res. Lett. 35, L22501 (2008).

    Article  Google Scholar 

  11. Nettles, M. et al. Step-wise changes in glacier flow speed coincide with calving and glacial earthquakes at Helheim Glacier, Greenland. Geophys. Res. Lett. 35, L24503 (2008).

    Article  Google Scholar 

  12. Murray, T. et al. Reverse glacier motion during iceberg calving and the cause of glacial earthquakes. Science 349, 305–308 (2015).

    Article  Google Scholar 

  13. Cates, M. E., Wittmer, J. P., Bouchaud, J. P. & Claudin, P. Jamming, force chains and fragile matter. Phys. Rev. Lett. 81, 1841–1844 (1998).

    Article  Google Scholar 

  14. Liu, A. J. & Nagel, S. R. The jamming transition and the marginally jammed solid. Annu. Rev. Condens. Matter Phys. 1, 347–369 (2010).

    Article  Google Scholar 

  15. Behringer, R. P. & Chakraborty, B. The physics of jamming for granular materials: a review. Rep. Prog. Phys. 82, 012601 (2018).

    Article  Google Scholar 

  16. Burton, J. C., Amundson, J. M., Cassotto, R., Kuo, C.-C. & Dennin, M. Quantifying flow and stress in ice mélange, the world’s largest granular material. Proc. Natl Acad. Sci. USA 115, 5105–5110 (2018).

    Article  Google Scholar 

  17. Robel, A. A. Thinning sea ice weakens buttressing force of iceberg mélange and promotes calving. Nat. Commun. 8, 14596 (2017).

    Article  Google Scholar 

  18. Amundson, J. M. & Burton, J. C. Quasi-static granular flow of ice mélange. J. Geophys. Res. Earth Surf. 123, 2243–2257 (2018).

    Article  Google Scholar 

  19. Waitukaitis, S. R., Roth, L. K., Vitelli, V. & Jaeger, H. M. Dynamic jamming fronts. Europhys. Lett. 102, 44001 (2013).

    Article  Google Scholar 

  20. Peters, I. R. et al. Dynamic jamming of iceberg-choked fjords. Geophys. Res. Lett. 42, 1122–1129 (2015).

    Article  Google Scholar 

  21. Jaeger, H. M. & Nagel, S. R. Physics of the granular state. Science 255, 1523–1532 (1992).

    Article  Google Scholar 

  22. Bi, D., Zhang, J., Chakraborty, B. & Behringer, R. P. Jamming by shear. Nature 480, 355–358 (2011).

    Article  Google Scholar 

  23. Thomas, A. L., Tang, Z., Daniels, K. E. & Vriend, N. M. Force fluctuations at the transition from quasi-static to inertial granular flow. Soft Matter 15, 8532–8542 (2019).

    Article  Google Scholar 

  24. Ferdowsi, B., Ortiz, C. P., Houssais, M. & Jerolmack, D. J. River-bed armouring as a granular segregation phenomenon. Nat. Commun. 8, 1363 (2017).

    Article  Google Scholar 

  25. King, M. D. et al. Seasonal to decadal variability in ice discharge from the Greenland Ice Sheet. Cryosphere 12, 3813–3825 (2018).

    Article  Google Scholar 

  26. Xie, S., Dixon, T. H., Holland, D. M., Voytenko, D. & Vaňková, I. Rapid iceberg calving following removal of tightly packed pro-glacial mélange. Nat. Commun. 10, 3250 (2019).

    Article  Google Scholar 

  27. Nghiem, S. V. et al. The extreme melt across the Greenland Ice Sheet in 2012. Geophys. Res. Lett. https://doi.org/10.1029/2012GL053611 (2012).

  28. Voytenko, D. et al. Acquisition of a 3-min, two-dimensional glacier velocity field with terrestrial radar interferometry. J. Glaciol. 63, 629–636 (2017).

    Article  Google Scholar 

  29. Cassotto, R. et al. Non-linear glacier response to calving events, Jakobshavn Isbræ, Greenland. J. Glaciol. 65, 39–54 (2018).

    Article  Google Scholar 

  30. Manning, M. L. & Liu, A. J. Vibrational modes identify soft spots in a sheared disordered packing. Phys. Rev. Lett. 107, 108302 (2011).

    Article  Google Scholar 

  31. Denisov, D. V., Lörincz, K. A., Uhl, J. T., Dahmen, K. A. & Schall, P. Universality of slip avalanches in flowing granular matter. Nat. Commun. 7, 10641 (2016).

    Article  Google Scholar 

  32. Langer, J. S. Shear-transformation-zone theory of yielding in athermal amorphous materials. Phys. Rev. E 92, 012318 (2015).

    Article  Google Scholar 

  33. Murray, T. et al. Dynamics of glacier calving at the ungrounded margin of Helheim Glacier, southeast Greenland. J. Geophys. Res. Earth Surf. 120, 964–982 (2015).

    Article  Google Scholar 

  34. Werner, C., Strozzi, T., Wiesmann, A. & Wegmuller, U. A real-aperture radar for ground-based differential interferometry. In Proc. 2008 IEEE International Geoscience and Remote Sensing Symposium III-210–III-213 (IEEE, 2008).

  35. Walter, J. I. et al. Oceanic mechanical forcing of a marine-terminating Greenland glacier. Ann. Glaciol. 53, 181–192 (2012).

    Article  Google Scholar 

  36. Holland, D. M. Air Temperature, Relative Humidity, and Others Collected from Automatic Weather Station Installed on Rock Outcrop in Jakobshavn Glacier Ice Front from 2007-10-13 to 2016-02-14 (NCEI Accession 0148760) (NCEI, 2016).

  37. Motyka, R. J., Dryer, W. P., Amundson, J., Truffer, M. & Fahnestock, M. Rapid submarine melting driven by subglacial discharge, LeConte Glacier, Alaska. Geophys. Res. Lett. 40, 5153–5158 (2013).

    Article  Google Scholar 

  38. Washam, P., Nicholls, K. W., Munchow, A. & Padman, L. Summer surface melt thins Petermann Gletscher Ice Shelf by enhancing channelized basal melt. J. Glaciol. 65, 662–674 (2019).

    Article  Google Scholar 

  39. Carr, J. R. et al. Basal topographic controls on rapid retreat of Humboldt Glacier, northern Greenland. J. Glaciol. 61, 137–150 (2015).

    Article  Google Scholar 

  40. Åkesson, H., Nisancioglu, K. H. & Nick, F. M. Impact of fjord geometry on grounding line stability. Front. Earth Sci. 6, 71 (2018).

    Article  Google Scholar 

  41. Todd, J. & Christoffersen, P. Are seasonal calving dynamics forced by buttressing from ice mélange or undercutting by melting? Outcomes from full-Stokes simulations of Store Glacier, West Greenland. Cryosphere 8, 2353–2365 (2014).

    Article  Google Scholar 

  42. Krug, J., Durand, G., Gagliardini, O. & Weiss, J. Modelling the impact of submarine frontal melting and ice mélange on glacier dynamics. Cryosphere 9, 989–1003 (2015).

    Article  Google Scholar 

  43. Johnson, P. A. & Jia, X. Nonlinear dynamics, granular media and dynamic earthquake triggering. Nature 437, 871–874 (2005).

    Article  Google Scholar 

  44. Rouet-Leduc, B. et al. Machine learning predicts laboratory earthquakes. Geophys. Res. Lett. 44, 9276–9282 (2017).

    Article  Google Scholar 

  45. Schoenholz, S. S., Cubuk, E. D., Sussman, D. M., Kaxiras, E. & Liu, A. J. A structural approach to relaxation in glassy liquids. Nat. Phys. 12, 469–471 (2016).

    Article  Google Scholar 

  46. Berthier, E., Porter, M. A. & Daniels, K. E. Forecasting failure locations in 2-dimensional disordered lattices. Proc. Natl Acad. Sci. USA 116, 16742–16749 (2019).

    Article  Google Scholar 

  47. Michlmayr, G., Cohen, D. & Or, D. Shear-induced force fluctuations and acoustic emissions in granular material. J. Geophys. Res. 118, 6086–6098 (2013).

    Article  Google Scholar 

  48. Driscoll, M. M. et al. The role of rigidity in controlling material failure. Proc. Natl Acad. Sci. USA 113, 10813–10817 (2016).

    Article  Google Scholar 

  49. Howat, I. M., Negrete, A. & Smith, B. E. MEaSUREs Greenland Ice Sheet Mapping Project (GIMP) Digital Elevation Model. NASA National Snow and Ice Data Center Distributed Active Archive Center (NSIDC, 2015); https://doi.org/10.5067/NV34YUIXLP9W

  50. Goldstein, R. M. & Werner, C. L. Radar interferogram filtering for geophysical applications. Geophys. Res. Lett. 25, 4035–4038 (1998).

    Article  Google Scholar 

  51. Goldstein, R. M., Zebker, H. A. & Werner, C. L. Satellite radar interferometry: two-dimensional phase unwrapping. Radio Sci. 23, 713–720 (1988).

    Article  Google Scholar 

  52. Fahnestock, M. et al. Rapid large-area mapping of ice flow using Landsat 8. Remote Sens. Environ. 185, 84–94 (2016).

    Article  Google Scholar 

  53. Bitzek, E., Koskinen, P., Gähler, F., Moseler, M. & Gumbsch, P. Structural relaxation made simple. Phys. Rev. Lett. 97, 170201 (2006).

    Article  Google Scholar 

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Acknowledgements

We thank A. Robel and T. Snow for stimulating conversations. We gratefully acknowledge CH2MHill Polar Service and Air Greenland for logistics support, NASA NNX08AN74G (M.A.F. and M.T.) for funding the field work, financial support from NASA Earth and Space Fellowship NNX14AL29H (R.K.C.), the National Science Foundation grant nos. DMR-1506446 (J.C.B.) and DMR-1506307 (J.M.A. and R.K.C.), and the Gordon and Betty Moore Foundation grants nos. GBMF2626 (M.A.F.) and GBMF2627 (M.T.) for the purchase of the TRIs.

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Authors and Affiliations

  1. Earth Science and Observation Center, Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, Boulder, CO, USA

    Ryan K. Cassotto

  2. Department of Physics, Emory University, Atlanta, GA, USA

    Justin C. Burton

  3. Department of Natural Sciences, University of Alaska Southeast, Juneau, AK, USA

    Jason M. Amundson

  4. Geophysical Institute, University of Alaska Fairbanks, Fairbanks, AK, USA

    Mark A. Fahnestock & Martin Truffer

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Contributions

R.K.C., J.M.A., M.A.F. and M.T. collected the TRI data. R.K.C. processed and analysed the data with input from all collaborators. J.C.B. created and completed the modelling component. R.K.C., J.C.B. and J.M.A. authored the manuscript with input from M.A.F. and M.T.

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Correspondence to Ryan K. Cassotto.

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The authors declare no competing interests.

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Peer review information Nature Geoscience thanks Douglas Jerolmack and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary Handling Editor: James Super.

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Extended data

Extended Data Fig. 1 The relationship between iceberg calving, ocean tides, line-of-sight ice mélange speeds, and glacier speeds.

The relationship between iceberg calving (black horizontal lines), (a) ocean tides, (b) line-of-sight ice mélange speeds and (c) glacier speeds with time ascending down along the y-axis in all panels. Most of the calving occurred during a spring tide when tidal amplitudes (mean difference between two high and two low tides each day) were high. Mélange speeds were similar in magnitude but more variable than glacier speeds, indicating proglacial mechanisms affect ice mélange flow. For nearly all calving events, an increase in mélange speeds occurred without coincident increase in glacier speeds; the sole exception was Aug 9 when a small calving event was precipitated by a partial loss of mélange flow coherence located downfjord of the sampled time-series.

Extended Data Fig. 2 Tidal oscillations in mélange flow for two different time periods in the early record.

(a) Tidal height measured ~5 km from the calving front and (b) Mélange 2D-derived speeds sampled along a centerline profile between Aug 1 19:02 and Aug 2 15:25. (c,d) same as (a,b) but for Aug 3 14:13 – Aug 5 9:43. Time ascends downward along the y-axis for all plots. The location of the profiles is shown in Extended Data Fig. 4.

Extended Data Fig. 3 Tidal oscillations in mélange flow for the time period Aug 6 20:52 – Aug 9 20:28.

(a) Tidal height measured ~5 km from the calving front. (b) Mélange 2D-derived speeds sampled along a center line profile shown in Extended Data Fig. 4. Time ascends downward along the y-axis for both plots.

Extended Data Fig. 4 TRI backscatter reference image.

TRI backscatter reference image showing the locations of the mélange 1D line-of-sight (maroon) and glacier speed (green; from Cassotto et al.29) time-series shown in Extended Data Fig. 1. The location of a center profile (orange) used to sample mélange 2D speeds in Extended Data Figs. 2 and 3 is also shown; blue points indicate 1-km distances along the profile.

Extended Data Fig. 5 Error Analysis.

Mean speeds between Aug 6 20:51 and Aug 8 19:21, 2012 derived from (a) PyCORR and (b) phase-based values. The difference between each method (phase-based minus PyCORR) shown in (c) map view and as a (d) histogram. The phase-based values are 1.7 m d−1 lower than PyCORR derived values with a standard deviation of 2.8 m d−1; we adopt the latter as the error in phase derived velocity fields.

Supplementary information

Supplementary Information

Legends for four Supplementary Videos and a brief discussion.

Supplementary Video 1

2D speed and velocity anomalies.

Supplementary Video 2

Divergence of velocity fields.

Supplementary Video 3

Time-lapse of 3-min TRI backscatter observations.

Supplementary Video 4

Time-lapse of 15-min camera observations.

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Cassotto, R.K., Burton, J.C., Amundson, J.M. et al. Granular decoherence precedes ice mélange failure and glacier calving at Jakobshavn Isbræ. Nat. Geosci. 14, 417–422 (2021). https://doi.org/10.1038/s41561-021-00754-9

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