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A consensus estimate for the ice thickness distribution of all glaciers on Earth

Nature Geoscience volume 12, pages 168–173 (2019)Cite this article

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Abstract

Knowledge of the ice thickness distribution of the world’s glaciers is a fundamental prerequisite for a range of studies. Projections of future glacier change, estimates of the available freshwater resources or assessments of potential sea-level rise all need glacier ice thickness to be accurately constrained. Previous estimates of global glacier volumes are mostly based on scaling relations between glacier area and volume, and only one study provides global-scale information on the ice thickness distribution of individual glaciers. Here we use an ensemble of up to five models to provide a consensus estimate for the ice thickness distribution of all the about 215,000 glaciers outside the Greenland and Antarctic ice sheets. The models use principles of ice flow dynamics to invert for ice thickness from surface characteristics. We find a total volume of 158 ± 41 × 103 km3, which is equivalent to 0.32 ± 0.08 m of sea-level change when the fraction of ice located below present-day sea level (roughly 15%) is subtracted. Our results indicate that High Mountain Asia hosts about 27% less glacier ice than previously suggested, and imply that the timing by which the region is expected to lose half of its present-day glacier area has to be moved forward by about one decade.

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Fig. 1: Overview of individual model contributions.
Fig. 2: Regional distribution of the calculated glacier ice volume.
Fig. 3: Overview of individual model contributions.

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Code availability

The codes used to generate individual results are available through the contact information from the original publications. Requests for further materials should be directed to D.F.

Data availability

The ice thickness distribution of all about 215,000 glaciers, as estimated with the individual models and the composite solution, is available at https://doi.org/10.3929/ethz-b-000315707.

References

  1. Vaughan, D. et al. in Climate Change 2013: The Physical Science Basis (eds Stocker, T. F. et al.) 317–382 (IPCC, Cambridge Univ. Press, 2013).

  2. Lambeck, K., Rouby, H., Purcell, A., Sun, Y. & Sambridge, M. Sea level and global ice volumes from the Last Glacial Maximum to the Holocene. Proc. Natl Acad. Sci. USA 111, 15296–15303 (2014).

    Article  Google Scholar 

  3. Kaser, G., Großhauser, M. & Marzeion, B. Contribution potential of glaciers to water availability in different climate regimes. Proc. Natl Acad. Sci. USA 107, 20223–20227 (2010).

    Article  Google Scholar 

  4. Rodell, M. et al. Emerging trends in global freshwater availability. Nature 557, 651–659 (2018).

    Article  Google Scholar 

  5. Marzeion, B., Jarosch, A. & Hofer, M. Past and future sea-level change from the surface mass balance of glaciers. Cryosphere 6, 1295–1322 (2012).

    Article  Google Scholar 

  6. Church, J. et al. in Climate Change 2013: The Physical Science Basis (eds Stocker, T. et al.) 1137–1216 (IPCC, Cambridge Univ. Press, 2013).

  7. Kraaijenbrink, P., Lutz, A., Bierkens, M. & Immerzeel, W. Impact of a 1.5° C global temperature rise on the glaciers of High Mountain Asia. Nature 549, 257–260 (2017).

    Article  Google Scholar 

  8. Huss, M. & Hock, R. Global-scale hydrological response to future glacier mass loss. Nat. Clim. Change 8, 135–140 (2018).

    Article  Google Scholar 

  9. Gabbi, J., Farinotti, D., Bauder, A. & Maurer, H. Ice volume distribution and implications on runoff projections in a glacierized catchment. Hydrol. Earth Syst. Sci. 16, 4543–4556 (2012).

    Article  Google Scholar 

  10. Huss, M. & Hock, R. A new model for global glacier change and sea-level rise. Front. Earth Sci. 3, 54 (2015).

    Article  Google Scholar 

  11. Nias, I., Cornford, S. & Payne, A. New mass conserving bedrock topography for Pine Island Glacier impacts simulated decadal rates of mass loss. Geophys. Res. Lett. 45, 3173–3181 (2018).

    Article  Google Scholar 

  12. Amundson, J. & Carroll, D. Effect of topography on subglacial discharge and submarine melting during tidewater glacier retreat. J. Geophys. Res. Earth Surf. 123, 66–79 (2017).

    Article  Google Scholar 

  13. Gärtner-Roer, I. et al. Glacier Thickness Database 2.0 (World Glacier Monitoring Service, 2016); https://doi.org/10.5904/wgms-glathida-2016-07

  14. Allen, C. IceBridge MCoRDS L2 Ice Thickness (NASA DAAC at the National Snow and Ice Data Center, 2010).

  15. Zamora, R., Uribe, J., Oberreuter, J. & Rivera, A. Ice thickness surveys of the southern Patagonian ice field using a low frequency ice penetrating radar system. In First IEEE Inter. Symp. Geosci. Remote Sensing (GRSS-CHILE) 1–4 (IEEE, 2017).

  16. Rutishauser, A., Maurer, H. & Bauder, A. Helicopter-borne ground-penetrating radar investigations on temperate alpine glaciers: a comparison of different systems and their abilities for bedrock mapping. Geophysics 81, WA119 (2016).

    Article  Google Scholar 

  17. Bahr, D. B., Pfeffer, W. T. & Kaser, G. A review of volume-area scaling of glaciers. Rev. Geophys. 53, 95–140 (2015).

    Article  Google Scholar 

  18. Dyurgerov, M. & Meier, M. Glaciers and the Changing Earth System: A 2004 Snapshot Institute of Arctic and Alpine Research Occasional Paper 58 (Univ. Colorado, 2005).

  19. Radić, V. & Hock, R. Regional and global volumes of glaciers derived from statistical upscaling of glacier inventory data. J. Geophys. Res. 115, F01010 (2010).

    Article  Google Scholar 

  20. Grinsted, A. An estimate of global glacier volume. Cryosphere 7, 141–151 (2013).

    Article  Google Scholar 

  21. Radić, V. et al. Regional and global projections of twenty-first century glacier mass changes in response to climate scenarios from global climate models. Clim. Dyn. 42, 37–58 (2014).

    Article  Google Scholar 

  22. Farinotti, D., Huss, M., Bauder, A., Funk, M. & Truffer, M. A method to estimate ice volume and ice thickness distribution of alpine glaciers. J. Glaciol. 55, 422–430 (2009).

    Article  Google Scholar 

  23. Morlighem, M. et al. A mass conservation approach for mapping glacier ice thickness. Geophys. Res. Lett. 38, L19503 (2011).

    Article  Google Scholar 

  24. Linsbauer, A., Paul, F. & Haeberli, W. Modeling glacier thickness distribution and bed topography over entire mountain ranges with GlabTop: application of a fast and robust approach. J. Geophys. Res. 117, F03007 (2012).

    Article  Google Scholar 

  25. McNabb, R. et al. Using surface velocities to calculate ice thickness and bed topography: a case study at Columbia Glacier, Alaska. J. Glaciol. 58, 1151–1164 (2012).

    Article  Google Scholar 

  26. van Pelt, W. J. J. et al. An iterative inverse method to estimate basal topography and initialize ice flow models. Cryosphere 7, 987–1006 (2013).

    Article  Google Scholar 

  27. Brinkerhoff, D. J., Aschwanden, A. & Truffer, M. Bayesian inference of subglacial topography using mass conservation. Front. Earth Sci. 4, 1–15 (2016).

    Article  Google Scholar 

  28. Clarke, G. K. C. et al. Ice volume and subglacial topography for western Canadian glaciers from mass balance fields, thinning rates, and a bed stress model. J. Clim. 26, 4282–4430 (2013).

    Article  Google Scholar 

  29. Frey, H. et al. Estimating the volume of glaciers in the Himalayan–Karakoram region using different methods. Cryosphere 8, 2313–2333 (2014).

    Article  Google Scholar 

  30. Huss, M. & Farinotti, D. Distributed ice thickness and volume of all glaciers around the globe. J. Geophys. Res. 117, F04010 (2012).

    Article  Google Scholar 

  31. Farinotti, D. et al. How accurate are estimates of glacier ice thickness? Results from ITMIX, the Ice Thickness Models Intercomparison eXperiment. Cryosphere 11, 949–970 (2017).

    Article  Google Scholar 

  32. Fürst, J. J. et al. Application of a two-step approach for mapping ice thickness to various glacier types on Svalbard. Cryosphere 11, 2003–2032 (2017).

    Article  Google Scholar 

  33. Maussion, F. et al. The Open Global Glacier Model (OGGM)v1.0. Geosci. Model Develop. Discuss. 2018, 1–33 (2018).

    Article  Google Scholar 

  34. Ramsankaran, R., Pandit, A. & Azam, M. Spatially distributed ice-thickness modelling for Chhota Shigri Glacier in western Himalayas, India. Int. J. Remote. Sens. 39, 3320–3343 (2018).

    Article  Google Scholar 

  35. RGI Consortium Randolph Glacier Inventory—A Dataset of Global Glacier Outlines: Version 6.0 (Global Land Ice Measurements from Space (GLIMS), 2017).

  36. Herman, F., Beaud, F., Champagnac, J.-D., Lemieux, J.-M. & Sternai, P. Glacial hydrology and erosion patterns: a mechanism for carving glacial valleys. Earth Planet. Sci. Lett. 310, 498–508 (2011).

    Article  Google Scholar 

  37. Haeberli, W. & Linsbauer, A. Global glacier volumes and sea level—small but systematic effects of ice below the surface of the ocean and of new local lakes on land. Cryosphere 7, 817–821 (2013).

    Article  Google Scholar 

  38. Immerzeel, W. W. & Bierkens, M. F. P. Asia's water balance. Nat. Geosci. 5, 841–842 (2012).

    Article  Google Scholar 

  39. Depoorter, M. A. et al. Calving fluxes and basal melt rates of Antarctic ice shelves. Nature 502, 89–92 (2013).

    Article  Google Scholar 

  40. Rignot, E. et al. Accelerated ice discharge from the Antarctic Peninsula following the collapse of Larsen B ice shelf. Geophys. Res. Lett. 31, L18401 (2004).

    Article  Google Scholar 

  41. Fürst, J. et al. The safety band of Antarctic ice shelves. Nat. Clim. Change 6, 479–482 (2016).

    Article  Google Scholar 

  42. Tachikawa, T., Hato, M., Kaku, M. & Iwasaki, A. Characteristics of ASTER GDEM version 2. In Proc. IEEE Int. Geosci. Remote Sensing Symp. (IGARSS) 2011 3657–3660 (IEEE, 2011).

  43. Liu, H, Jezek, K, Li, B. & Zhao, Z. Radarsat Antarctic Mapping Project Digital Elevation Model, Version 2 (NASA National Snow and Ice Data Center Distributed Active Archive Center, 2015).

  44. Bahr, D. B., Pfeffer, W. T. & Kaser, G. Glacier volume estimation as an ill-posed inversion. J. Glaciol. 60, 922934 (2014).

    Article  Google Scholar 

  45. Jarvis, J., Reuter, H., Nelson, A. & Guevara, E. Hole-Filled SRTM for the Globe Version 4 (CGIAR Consortium for Spatial Information, 2008).

  46. Liu, S. et al. Glacier retreat as a result of climate warming and increased precipitation in the Tarim river basin, northwest China. Ann. Glaciol. 43, 91–96 (2006).

    Article  Google Scholar 

  47. Porter, C. et al. ArcticDEM V1 (Harvard Dataverse, 2017); https://doi.org/10.7910/DVN/OHHUKH

  48. de Ferranti, J. A Worldwide 3 Arc Seconds DEM (2014); http://viewfinderpanoramas.org/dem3.html

  49. Fürst, J. et al. The ice-free topography of Svalbard. Geophys. Res. Lett. 45, 760–711 (2018).

    Article  Google Scholar 

  50. Hartung, J., Knapp, G. & Sinha, B. Statistical Meta-analysis with Applications (John Wiley & Sons, Hoboken, 2008).

    Book  Google Scholar 

  51. Conkright, M. et al. World Ocean Atlas 2001: Objective Analyses, Data Statistics, and Figures, CD-ROM Documentation 17 (National Oceanographic Data Center, Silver Spring, 2002).

    Google Scholar 

  52. Dee, D. et al. The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Q. J. R. Meteorol. Soc 137, 553–597 (2011).

    Article  Google Scholar 

  53. Taylor, K., Stouffer, R. & Meehl, G. An overview of CMIP5 and the experiment design. Bull. Am. Meteorol. Soc. 93, 485–498 (2012).

    Article  Google Scholar 

  54. Meinshausen, M. et al. The RCP greenhouse gas concentrations and their extensions from 1765 to 2300. Climatic Change 109, 213–241 (2011).

    Article  Google Scholar 

  55. Rignot, E, Mouginot, J. & Scheuchl, B. MEaSUREs InSAR-Based Antarctica Ice Velocity Map, Version 2 (NASA National Snow and Ice Data Center Distributed Active Archive Center, 2017).

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Acknowledgements

The contribution from J.J.F. was supported by the German Research Foundation (DFG grant no. FU1032/1-1), with numerical simulations facilitated by the high-performance computing centre at the University of Erlangen-Nuremberg (Regionales Rechenzentrum Erlangen (RRZE)). The support form R. Ramsankaran’s research team at the Indian Institute of Technology Bombay is acknowledged. We thank the International Association of Cryospheric Sciences (IACS), co-chairs L. M. Andreassen and H. Li, and the members of the IACS Working Group on Glacier Ice Thickness Estimation for the support during the work. The analyses were performed in the frame of the Working Group’s Global Glacier Thickness Initiative (G2TI).

Author information

Authors and Affiliations

  1. Laboratory of Hydraulics, Hydrology and Glaciology (VAW), ETH Zurich, Zurich, Switzerland

    Daniel Farinotti, Matthias Huss & Johannes Landmann

  2. Swiss Federal Institute for Forest, Snow and Landscape Research (WSL), Birmensdorf, Switzerland

    Daniel Farinotti & Johannes Landmann

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

    Matthias Huss & Horst Machguth

  4. Institute of Geography, Friedrich-Alexander-University Erlangen-Nuremberg (FAU), Erlangen, Germany

    Johannes J. Fürst

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

    Horst Machguth

  6. Institute of Atmospheric and Cryospheric Sciences, University of Innsbruck, Innsbruck, Austria

    Fabien Maussion

  7. Interdisciplinary Programme in Climate Studies, Indian Institute of Technology Bombay, Mumbai, India

    Ankur Pandit

  8. Hydro-Remote Sensing Applications (H-RSA) Group, Department of Civil Engineering, Indian Institute of Technology Bombay, Mumbai, India

    Ankur Pandit

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  1. Daniel Farinotti
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Contributions

D.F. conceived the study, performed the analyses of the results and drafted the manuscript, to which all the authors contributed. M.H., J.L. and D.F. prepared the necessary input data. M.H., J.J.F., H.M., F.M. and A.P. performed the calculations with individual models. M.H. and D.F. performed the GloGEM and Antarctic ice-discharge calculations, respectively.

Corresponding author

Correspondence to Daniel Farinotti.

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Farinotti, D., Huss, M., Fürst, J.J. et al. A consensus estimate for the ice thickness distribution of all glaciers on Earth. Nat. Geosci. 12, 168–173 (2019). https://doi.org/10.1038/s41561-019-0300-3

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