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Centennial glacier retreat as categorical evidence of regional climate change


The near-global retreat of glaciers over the last century provides some of the most iconic imagery for communicating the reality of anthropogenic climate change to the public. Surprisingly, however, there has not been a quantitative foundation for attributing the retreats to climate change, except in the global aggregate. This gap, between public perception and scientific basis, is due to uncertainties in numerical modelling and the short length of glacier mass-balance records. Here we present a method for assessing individual glacier change based on the signal-to-noise ratio, a robust metric that is insensitive to uncertainties in glacier dynamics. Using only meteorological and glacier observations, and the characteristic decadal response time of glaciers, we demonstrate that observed retreats of individual glaciers represent some of the highest signal-to-noise ratios of climate change yet documented. Therefore, in many places, the centennial-scale retreat of the local glaciers does indeed constitute categorical evidence of climate change.

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Figure 1: The global record of glacier lengths5, for 158 glaciers with 20 or more individual observations (shown as dots).
Figure 2: The response of idealized glaciers to climate.
Figure 3: Analysis for Hintereisferner (Austrian Alps, 46.8° N, 10.8° E).
Figure 4: Analysis of glacier retreat from around the world (see Fig. 1).


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We are grateful to P. Green, K. Armour, D. Battisti and E. Steig for valuable comments and conversations. F.H. thanks the Institute of Atmospheric and Cryospheric Sciences, University of Innsbruck for financial support.

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G.H.R., M.B.B. and F.H. planned the analyses, which G.H.R. performed. All authors contributed to the interpretation of the results and to writing the manuscript.

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Correspondence to Gerard H. Roe.

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The authors declare no competing financial interests.

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Roe, G., Baker, M. & Herla, F. Centennial glacier retreat as categorical evidence of regional climate change. Nature Geosci 10, 95–99 (2017).

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