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Historical glacier change on Svalbard predicts doubling of mass loss by 2100.
- Source :
-
Nature [Nature] 2022 Jan; Vol. 601 (7893), pp. 374-379. Date of Electronic Publication: 2022 Jan 19. - Publication Year :
- 2022
-
Abstract
- The melting of glaciers and ice caps accounts for about one-third of current sea-level rise <superscript>1-3</superscript> , exceeding the mass loss from the more voluminous Greenland or Antarctic Ice Sheets <superscript>3,4</superscript> . The Arctic archipelago of Svalbard, which hosts spatial climate gradients that are larger than the expected temporal climate shifts over the next century <superscript>5,6</superscript> , is a natural laboratory to constrain the climate sensitivity of glaciers and predict their response to future warming. Here we link historical and modern glacier observations to predict that twenty-first century glacier thinning rates will more than double those from 1936 to 2010. Making use of an archive of historical aerial imagery <superscript>7</superscript> from 1936 and 1938, we use structure-from-motion photogrammetry to reconstruct the three-dimensional geometry of 1,594 glaciers across Svalbard. We compare these reconstructions to modern ice elevation data to derive the spatial pattern of mass balance over a more than 70-year timespan, enabling us to see through the noise of annual and decadal variability to quantify how variables such as temperature and precipitation control ice loss. We find a robust temperature dependence of melt rates, whereby a 1 °C rise in mean summer temperature corresponds to a decrease in area-normalized mass balance of -0.28 m yr <superscript>-1</superscript> of water equivalent. Finally, we design a space-for-time substitution <superscript>8</superscript> to combine our historical glacier observations with climate projections and make first-order predictions of twenty-first century glacier change across Svalbard.<br /> (© 2022. The Author(s), under exclusive licence to Springer Nature Limited.)
Details
- Language :
- English
- ISSN :
- 1476-4687
- Volume :
- 601
- Issue :
- 7893
- Database :
- MEDLINE
- Journal :
- Nature
- Publication Type :
- Academic Journal
- Accession number :
- 35046605
- Full Text :
- https://doi.org/10.1038/s41586-021-04314-4