Two decades of glacier mass loss along the Andes

An Author Correction to this article was published on 01 September 2020

This article has been updated

Abstract

Andean glaciers are among the fastest shrinking and largest contributors to sea level rise on Earth. They also represent crucial water resources in many tropical and semi-arid mountain catchments. Yet the magnitude of the recent ice loss is still debated. Here we present Andean glacier mass changes (from 10° N to 56° S) between 2000 and 2018 using time series of digital elevation models derived from ASTER stereo images. The total mass change over this period was −22.9 ± 5.9 Gt yr−1 (−0.72 ± 0.22 m w.e. yr−1 (m w.e., metres of water equivalent)), with the most negative mass balances in the Patagonian Andes (−0.78 ± 0.25 m w.e. yr−1) and the Tropical Andes (−0.42 ± 0.24 m w.e. yr−1), compared to relatively moderate losses (−0.28 ± 0.18 m w.e. yr−1) in the Dry Andes. Subperiod analysis (2000–2009 versus 2009–2018) revealed a steady mass loss in the tropics and south of 45° S. Conversely, a shift from a slightly positive to a strongly negative mass balance was measured between 26 and 45° S. In the latter region, the drastic glacier loss in recent years coincides with the extremely dry conditions since 2010 and partially helped to mitigate the negative hydrological impacts of this severe and sustained drought. These results provide a comprehensive, high-resolution and multidecadal data set of recent Andes-wide glacier mass changes that constitutes a relevant basis for the calibration and validation of hydrological and glaciological models intended to project future glacier changes and their hydrological impacts.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Fig. 1: Andes-wide glacier mass balance rates averaged by 1° latitude and 1° longitude tiles.
Fig. 2: Delimitation of seven subregions and altitudinal distribution of glacier elevation change.
Fig. 3: Glacier mass change rate estimates from multiple methodologies.
Fig. 4: The seven main river basins used in the hydrological analyses.

Data availability

Rate of elevation change maps are distributed through PANGAEA platform (https://doi.pangaea.de/10.1594/PANGAEA.903618). Individual glacier mass balances will be provided through the World Glacier Monitoring Service database (https://wgms.ch/data_exploration/). The code used to generate ASTER DEMs from the freely available 1A images can be downloaded at https://github.com/FannyBrun/ASTER_DEM_from_L1A. Individual ASTER DEMs are also available upon request to the corresponding author (I.D.).

Change history

  • 01 September 2020

    An amendment to this paper has been published and can be accessed via a link at the top of the paper.

References

  1. 1.

    Clapperton, C. M. The glaciation of the Andes. Quat. Sci. Rev. 2, 83–155 (1983).

    Google Scholar 

  2. 2.

    Garreaud, R. D., Vuille, M., Compagnucci, R. & Marengo, J. Present-day South American climate. Palaeogeogr. Palaeoclimatol. Palaeoecol. 281, 180–195 (2009).

    Google Scholar 

  3. 3.

    Bamber, J., Westaway, R., Marzeion, B. & Wouters, B. The land ice contribution to sea level during the satellite era. Environ. Res. Lett. 13, 063008 (2018).

    Google Scholar 

  4. 4.

    Gardner, A. S. et al. A reconciled estimate of glacier contributions to sea level rise: 2003 to 2009. Science 340, 852–857 (2013).

    Google Scholar 

  5. 5.

    Jacob, T., Wahr, J., Pfeffer, W. T. & Swenson, S. Recent contributions of glaciers and ice caps to sea level rise. Nature 482, 514–518 (2012).

    Google Scholar 

  6. 6.

    Marzeion, B., Leclercq, P. W., Cogley, J. G. & Jarosch, A. H. Brief communication: global reconstructions of glacier mass change during the 20th century are consistent. Cryosphere 9, 2399–2404 (2015).

    Google Scholar 

  7. 7.

    Reager, J. T. et al. A decade of sea level rise slowed by climate-driven hydrology. Science 351, 699–703 (2016).

    Google Scholar 

  8. 8.

    Glasser, N. F., Harrison, S., Jansson, K. N., Anderson, K. & Cowley, A. Global sea-level contribution from the Patagonian icefields since the Little Ice Age maximum. Nat. Geosci. 4, 303–307 (2011).

    Google Scholar 

  9. 9.

    Zemp, M. et al. Global glacier mass changes and their contributions to sea-level rise from 1961 to 2016. Nature 568, 382–386 (2019).

    Google Scholar 

  10. 10.

    Buytaert, W. et al. Glacial melt content of water use in the tropical Andes. Environ. Res. Lett. 12, 114014 (2017).

    Google Scholar 

  11. 11.

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

    Google Scholar 

  12. 12.

    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).

    Google Scholar 

  13. 13.

    Huss, M. et al. Toward mountains without permanent snow and ice. Earth’s Future 5, 418–435 (2017).

    Google Scholar 

  14. 14.

    Vuille, M. et al. Rapid decline of snow and ice in the tropical Andes—impacts, uncertainties and challenges ahead. Earth-Sci. Rev. 176, 195–213 (2018).

    Google Scholar 

  15. 15.

    Cogley, J. G. Geodetic and direct mass-balance measurements: comparison and joint analysis. Ann. Glaciol. 50, 96–100 (2009).

    Google Scholar 

  16. 16.

    Mernild, S. H. et al. Mass loss and imbalance of glaciers along the Andes Cordillera to the sub-Antarctic islands. Glob. Planet. Change 133, 109–119 (2015).

    Google Scholar 

  17. 17.

    Rabatel, A. et al. Current state of glaciers in the tropical Andes: a multi-century perspective on glacier evolution and climate change. Cryosphere 7, 81–102 (2013).

    Google Scholar 

  18. 18.

    Zemp, M. et al. Historically unprecedented global glacier decline in the early 21st century. J. Glaciol. 61, 745–762 (2015).

    Google Scholar 

  19. 19.

    Rignot, E., Rivera, A. & Casassa, G. Contribution of the Patagonia Icefields of South America to sea level rise. Science 302, 434–437 (2003).

    Google Scholar 

  20. 20.

    Malz, P. et al. Elevation and mass changes of the Southern Patagonia Icefield derived from TanDEM-X and SRTM data. Remote Sens. 10, 188 (2018).

    Google Scholar 

  21. 21.

    Melkonian, A. K. et al. Satellite-derived volume loss rates and glacier speeds for the Cordillera Darwin Icefield, Chile. Cryosphere 7, 823–839 (2013).

    Google Scholar 

  22. 22.

    Braun, M. H. et al. Constraining glacier elevation and mass changes in South America. Nat. Clim. Change 9, 130–136 (2019).

    Google Scholar 

  23. 23.

    Ivins, E. R. et al. On‐land ice loss and glacial isostatic adjustment at the Drake Passage: 2003–2009. J. Geophys. Res. 116, B02403 (2011).

    Google Scholar 

  24. 24.

    Richter, A. et al. Crustal deformation across the Southern Patagonian Icefield observed by GNSS. Earth Planet. Sci. Lett. 452, 206–215 (2016).

    Google Scholar 

  25. 25.

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

    Google Scholar 

  26. 26.

    Mernild, S. & Wilson, R. The Andes Cordillera. Part III: glacier surface mass balance and contribution to sea level rise (1979-2014). Int. J. Climatol. 37, 3154–3174 (2016).

    Google Scholar 

  27. 27.

    Collao-Barrios, G. et al. Ice flow modelling to constrain the surface mass balance and ice discharge of San Rafael Glacier, Northern Patagonia Icefield. J. Geol. 64, 568–582 (2018).

    Google Scholar 

  28. 28.

    Schaefer, M., Machguth, H., Falvey, M., Casassa, G. & Rignot, E. Quantifying mass balance processes on the Southern Patagonia Icefield. Cryosphere 9, 25–35 (2015).

    Google Scholar 

  29. 29.

    Brun, F., Berthier, E., Wagnon, P., Kääb, A. & Treichler, D. A spatially resolved estimate of High Mountain Asia glacier mass balances from 2000 to 2016. Nat. Geosci. 10, 668–673 (2017).

    Google Scholar 

  30. 30.

    Berthier, E., Larsen, C., Durkin, W. J., Willis, M. J. & Pritchard, M. E. Brief communication: unabated wastage of the Juneau and Stikine icefields (southeast Alaska) in the early 21st century. Cryosphere 12, 1523–1530 (2018).

    Google Scholar 

  31. 31.

    Dussaillant, I., Berthier, E. & Brun, F. GIeodetic mass balance of the Northern Patagonian Icefield from 2000 to 2012 using two independent methods. Front. Earth Sci. 6, 8 (2018).

    Google Scholar 

  32. 32.

    Masiokas, M. H. et al. Glacier fluctuations in extratropical South America during the past 1000 years. Palaeogeogr. Palaeoclimatol. Palaeoecol. 281, 242–268 (2009).

    Google Scholar 

  33. 33.

    Sagredo, E. A. & Lowell, T. V. Climatology of Andean glaciers: a framework to understand glacier response to climate change. Glob. Planet. Change 86, 101–109 (2012).

    Google Scholar 

  34. 34.

    Jaber, W. A., Floricioiu, D. & Rott, H. Geodetic mass balance of the Patagonian icefields derived from SRTM and TanDEM-X data. In 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS) 342–345 (IEEE, 2016); https://doi.org/10.1109/IGARSS.2016.7729082

  35. 35.

    Rabatel, A. et al. Toward an imminent extinction of Colombian glaciers? Geogr. Annal. A 100, 75–95 (2017).

    Google Scholar 

  36. 36.

    Cook, S. J., Kougkoulos, I., Edwards, L. A., Dortch, J. & Hoffmann, D. Glacier change and glacial lake outburst flood risk in the Bolivian Andes. Cryosphere 10, 2399–2413 (2016).

    Google Scholar 

  37. 37.

    Paul, F. & Mölg, N. Hasty retreat of glaciers in northern Patagonia from 1985 to 2011. J. Glaciol. 60, 1033–1043 (2014).

    Google Scholar 

  38. 38.

    Burger, F. et al. Interannual and decadal variability in glacier contribution to runoff from high-elevation Andean catchments: understanding the role of debris cover in glacier hydrology. Hydrol. Process. 33, 214–229 (2019).

    Google Scholar 

  39. 39.

    Farías-Barahona, D. et al. Geodetic mass balances and area changes of Echaurren Norte glacier (Central Andes, Chile) between 1955 and 2015. Remote Sens. 11, 260 (2019).

    Google Scholar 

  40. 40.

    Masiokas, M. H. et al. Reconstructing the annual mass balance of the Echaurren Norte glacier (Central Andes, 33.5° S) using local and regional hydroclimatic data. The Cryosphere 10, 927–940 (2016).

    Google Scholar 

  41. 41.

    Wouters, B., Gardner, A. S. & MoHoldt, G. Global glacier mass loss during the GRACE satellite mission (2002–2016). Front. Earth Sci. 7, 96 (2019).

    Google Scholar 

  42. 42.

    Dietrich, R. et al. Rapid crustal uplift in Patagonia due to enhanced ice loss. Earth Planet. Sci. Lett. 289, 22–29 (2010).

    Google Scholar 

  43. 43.

    Ivins, E. R. et al. On-land ice loss and glacial isostatic adjustment at the Drake Passage: 2003–2009. J. Geophys. Res. 116, B02403 (2011).

    Google Scholar 

  44. 44.

    Pritchard, H. D. Asia’s shrinking glaciers protect large populations from drought stress. Nature 569, 649–654 (2019).

    Google Scholar 

  45. 45.

    Radić, V. & Hock, R. Glaciers in the Earth’s hydrological cycle. Assessments of glacier mass and runoff changes on global and regional scales. Surv. Geophys. 35, 813–837 (2014).

    Google Scholar 

  46. 46.

    Lambrecht, A. & Mayer, C. Temporal variability of the non-steady contribution from glaciers to water discharge in western Austria. J. Hydrol. 376, 353–361 (2009).

    Google Scholar 

  47. 47.

    Garreaud, R. D. et al. The 2010–2015 megadrought in central Chile: impacts on regional hydroclimate and vegetation. Hydrol. Earth Syst. Sci. 21, 6307–6327 (2017).

    Google Scholar 

  48. 48.

    Rivera, J. A., Penalba, O. C., Villalba, R. & Araneo, D. C. Spatio-temporal patterns of the 2010–2015 extreme hydrological drought across the Central Andes, Argentina. Water 9, 652 (2017).

    Google Scholar 

  49. 49.

    Gascoin, S. et al. Glacier contribution to streamflow in two headwaters of the Huasco River, Dry Andes of Chile. Cryosphere 5, 1099–1113 (2011).

    Google Scholar 

  50. 50.

    Ragettli, S. & Pellicciotti, F. Calibration of a physically based, spatially distributed hydrological model in a glacierized basin: on the use of knowledge from glaciometeorological processes to constrain model parameters. Water Resour. Res. 48, W03509 (2012).

    Google Scholar 

  51. 51.

    Kääb, A., Treichler, D., Nuth, C. & Berthier, E. Brief communication: contending estimates of 2003–2008 glacier mass balance over the Pamir–Karakoram–Himalaya. Cryosphere 9, 557–564 (2015).

    Google Scholar 

  52. 52.

    Nuimura, T., Fujita, K., Yamaguchi, S. & Sharma, R. R. Elevation changes of glaciers revealed by multitemporal digital elevation models calibrated by GPS survey in the Khumbu region, Nepal Himalaya, 1992-2008. J. Glaciol. 58, 648–656 (2012).

    Google Scholar 

  53. 53.

    Wang, D. & Kääb, A. Modeling glacier elevation change from DEM time series. Remote Sens. 7, 10117–10142 (2015).

    Google Scholar 

  54. 54.

    Willis, M. J., Melkonian, A. K., Pritchard, M. E. & Ramage, J. M. Ice loss rates at the Northern Patagonian Icefield derived using a decade of satellite remote sensing. Remote Sens. Environ. 117, 184–198 (2012).

    Google Scholar 

  55. 55.

    Earthdata (NASA, accessed 3 August 2018); https://earthdata.nasa.gov/

  56. 56.

    Shean, D. E. et al. An automated, open-source pipeline for mass production of digital elevation models (DEMs) from very-high-resolution commercial stereo satellite imagery. ISPRS J. Photogram. Remote Sens. 116, 101–117 (2016).

    Google Scholar 

  57. 57.

    Nuth, C. & Kääb, A. Co-registration and bias corrections of satellite elevation data sets for quantifying glacier thickness change. Cryosphere 5, 271–290 (2011).

    Google Scholar 

  58. 58.

    Jaber, W. A., Floricioiu, D., Rott, H. & Eineder, M. Surface elevation changes of glaciers derived from SRTM and TanDEM-X DEM differences. In 2013 IEEE International Geoscience and Remote Sensing Symposium (IGARSS) 1893–1896 (IEEE, 2013); https://doi.org/10.1109/IGARSS.2013.6723173

  59. 59.

    McNabb, R., Nuth, C., Kääb, A. & Girod, L. Sensitivity of glacier volume change estimation to DEM void interpolation. Cryosphere 13, 895–910 (2019).

    Google Scholar 

  60. 60.

    Huss, M. Density assumptions for converting geodetic glacier volume change to mass change. Cryosphere 7, 877–887 (2013).

    Google Scholar 

  61. 61.

    Lehner, B. & Döll, P. Development and validation of a global database of lakes, reservoirs and wetlands. J. Hydrol. 296, 1–22 (2004).

    Google Scholar 

  62. 62.

    OpenStreetMap (OpenStreetMap, accessed 8 December 2018); https://www.openstreetmap.org/copyright

  63. 63.

    Pfeffer, W. T. et al. The Randolph Glacier Inventory: a globally complete inventory of glaciers. J. Glaciol. 60, 537–552 (2014).

    Google Scholar 

  64. 64.

    Fischer, M., Huss, M. & Hoelzle, M. Surface elevation and mass changes of all Swiss glaciers 1980–2010. Cryosphere 9, 525–540 (2015).

    Google Scholar 

  65. 65.

    Rolstad, C., Haug, T. & Denby, B. Spatially integrated geodetic glacier mass balance and its uncertainty based on geostatistical analysis: application to the western Svartisen ice cap, Norway. J. Glaciol. 55, 666–680 (2009).

    Google Scholar 

  66. 66.

    Menounos, B. et al. Heterogeneous changes in western North American glaciers linked to decadal variability in zonal wind strength. Geophys. Res. Lett. 46, 200–209 (2019).

    Google Scholar 

Download references

Acknowledgements

We acknowledge the French Space Agency (CNES) and the Région Occitanie for PhD fellowship to I.D. E.B. also acknowledges the support from the CNES and the French Programme National de Télédétection Spatiale grant PNTS-2016-01. L.R., P.P. and M.M. acknowledge the support from Agencia de Promoción Científica (projects PICT 2010-1438 and PICT 2014-1794) and CONICET. ASTER images are courtesy of NASA/METI/AIST/Japan Space systems and the US/Japan ASTER Science Team. This work was only possible thanks to the GLIMS project (www.glims.org/) which allowed the population of a vast archive of freely available ASTER stereo images over the glaciers. We thank the Ames Stereo Pipeline support and developer teams for their help. Most of the computation was performed using the Froggy platform of the CIMENT infrastructure (http://ciment.ujf-grenoble.fr), supported by the Rhone-Alpes region (grant CPER07_13 CIRA), the OSUG@2020 labex (reference ANR10 LABX56) and the Equip@Meso project (reference ANR-10-EQPX-29-01) of the Programme Investissements d’Avenir supervised by the French Agence National pour la Recherche. We are grateful to K. Moxham for reviewing the English.

Author information

Affiliations

Authors

Contributions

I.D. and E.B. designed the study. I.D. performed the ASTER DEM analysis with inputs from F.B., R.H. and E.B. M.M. made the streamflow analysis. All the authors contributed to the interpretation of the results. I.D. led the writing of the paper and all the other co-authors contributed to it.

Corresponding author

Correspondence to I. Dussaillant.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Supplementary Information

Supplementary Information.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Dussaillant, I., Berthier, E., Brun, F. et al. Two decades of glacier mass loss along the Andes. Nat. Geosci. 12, 802–808 (2019). https://doi.org/10.1038/s41561-019-0432-5

Download citation

Further reading

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