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Anthropogenic warming forces extreme annual glacier mass loss

Nature Climate Change volume 10, pages 856–861 (2020)Cite this article

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Abstract

Glaciers are unique indicators of climate change. While recent global-scale glacier decline has been attributed to anthropogenic forcing, direct links between human-induced climate warming and extreme glacier mass-loss years have not been documented. Here we apply event attribution methods to document this at the regional scale, targeting the highest mass-loss years (2011 and 2018) across New Zealand’s Southern Alps. Glacier mass balance is simulated using temperature and precipitation from multiple climate model ensembles. We estimate extreme mass loss was at least six times (2011) and ten times (2018) (>90% confidence) more likely to occur with anthropogenic forcing than without. This increased likelihood is driven by present-day temperatures ~1.0 °C above the pre-industrial average, confirming a connection between anthropogenic emissions and high annual ice loss. These results suggest that as warming and extreme heat events continue and intensify, there will be an increasingly visible human fingerprint on extreme glacier mass-loss years in the coming decades.

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Fig. 1: Increasing extreme mass-loss measurements in recent decades.
Fig. 2: Annual Brewster and Rolleston Glacier mass-balance and snowline probability distributions.
Fig. 3: Likelihoods of glacier mass loss with natural and anthropogenic forcing.
Fig. 4: Annual snowline probability distributions.

Data availability

Global glacier mass-balance data in Fig. 1 and Extended Data Figure 1 are available from the World Glacier Monitoring Service at https://wgms.ch/products_ref_glaciers/. See Supplementary Table 4 for 2011 and 2018 mass-balance and snowline measurements. Snowlines through 2015 are available from National Institute of Water and Atmospheric Research (NIWA) at https://sirg.org.nz/about/annual-end-of-snummer-snowline-survey/. CMIP5 GCM output is available from public repositories, including https://esgf-node.llnl.gov/search/cmip5/. CESM output is available from the CESM/UCAR repository at http://www.cesm.ucar.edu/projects/community-projects/LENS/data-sets.html. VCSN data are available from https://data.niwa.co.nz/#/home. Raw figures are available from https://doi.org/10.6084/m9.figshare.12315458.v1.

Code availability

All code is available from https://github.com/lvargo13/glacier_attribution (ref. 52).

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Acknowledgements

This work was supported by NIWA Strategic Science Internal Funding of the ‘Climate Present and Past’ project CAOA1901, a subcontract to Victoria University of Wellington from NIWA for ‘Structure from Motion of Southern Alps glaciers’ and a Victoria University of Wellington Doctoral Scholarship. A.D.K. received support from the Australian Research Council (DE180100638). We thank N. Cullen and P. Sirguey for sharing Brewster mass-balance data, and T. Kerr and H. Purdie for sharing Rolleston mass-balance data. We acknowledge the climate modelling groups that contributed model output to CMIP5 and the groups measuring glacier mass balance that makes up the data in Fig. 1. We thank R. Hock, S. Eaves and C. Lukens for their input, T. Chinn, A. Willsman and A. Woods for their work on the snowline survey.

Author information

Authors and Affiliations

  1. Antarctic Research Centre, Victoria University of Wellington, Wellington, New Zealand

    Lauren J. Vargo, Brian M. Anderson, Ruzica Dadić & Huw J. Horgan

  2. School of Geography, Environment and Earth Sciences, Victoria University of Wellington, Wellington, New Zealand

    Lauren J. Vargo & Huw J. Horgan

  3. School of Earth, Atmosphere & Environment, Monash University, Melbourne, Victoria, Australia

    Andrew N. Mackintosh

  4. School of Earth Sciences and ARC Centre of Excellence for Climate Extremes, University of Melbourne, Melbourne, Victoria, Australia

    Andrew D. King

  5. National Institute of Water and Atmospheric Research, Auckland, New Zealand

    Andrew M. Lorrey

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Contributions

L.J.V., B.M.A., H.J.H. and R.D. developed the glacier model. L.J.V. performed the analysis and led the writing. All authors contributed to the design of the study, discussed the results and contributed to writing of the manuscript.

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Correspondence to Lauren J. Vargo.

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Extended data

Extended Data Fig. 1 Global glaciers, increasing extreme mass-loss years in recent decades, and study area.

Full map: All global glaciers53 (black), including all glaciers with >30 years of mass-balance measurements1 (open black circles). Each colored square represents one extreme mass-loss year, with the color showing the timing, by decade. Extreme mass-loss years are defined as the 90th percentile of negative mass balances for each individual glacier. Inset: Glaciers in the Southern Alps of New Zealand53 (black), including the subset of glaciers used in this study (blue).

Extended Data Fig. 2 Changes in GCM temperature and precipitation output between natural and present climates.

Temperature (top; ∘C) and precipitation (bottom; %) changes for present-world scenarios compared with natural-world scenarios. For each model or CESM ensemble member, values are averaged for all ten glaciers. Present world is defined as RCP8.5 (April 2006 – March 2026) for both CMIP5 and CESM. The natural world is defined as HistoricalNat (April 1901 – March 2005) for CMIP5 and the CESM LE control run (April year 1 – March year 1800) for CESM.

Supplementary information

Supplementary Information

Supplementary Figs. 1–4, Tables 1–4, discussions and references.

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Vargo, L.J., Anderson, B.M., Dadić, R. et al. Anthropogenic warming forces extreme annual glacier mass loss. Nat. Clim. Chang. 10, 856–861 (2020). https://doi.org/10.1038/s41558-020-0849-2

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