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Discussion papers | Copyright
https://doi.org/10.5194/tc-2018-126
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 02 Jul 2018

Research article | 02 Jul 2018

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This discussion paper is a preprint. It is a manuscript under review for the journal The Cryosphere (TC).

Interannual snow accumulation variability on glaciers derived from repeat, spatially extensive ground-penetrating radar surveys

Daniel McGrath1, Louis Sass2, Shad O'Neel2, Chris McNeil2, Salvatore G. Candela3, Emily H. Baker2, and Hans-Peter Marshall4 Daniel McGrath et al.
  • 1Department of Geosciences, Colorado State University, Fort Collins, CO
  • 2U.S. Geological Survey Alaska Science Center, Anchorage, AK
  • 3School of Earth Sciences and Byrd Polar Research Center, Ohio State University, Columbus, OH
  • 4Department of Geosciences, Boise State University, Boise, ID

Abstract. There is significant uncertainty regarding the spatiotemporal distribution of seasonal snow on glaciers, despite being a fundamental component of glacier mass balance. To address this knowledge gap, we collected repeat, spatially extensive high-frequency ground-penetrating radar (GPR) observations on two glaciers in Alaska for five consecutive years. GPR measurements showed steep snow water equivalent (SWE) elevation gradients at both sites; continental Gulkana Glacier’s SWE gradient averaged 115mm 100m−1 and maritime Wolverine Glacier’s gradient averaged 440mm 100m−1 (over >1000m). We extrapolated GPR point observations across the glacier surface using terrain parameters derived from digital elevation models as predictor variables in two statistical models (stepwise multivariable linear regression and regression trees). Elevation and proxies for wind redistribution had the greatest explanatory power, and exhibited relatively time-constant coefficients over the study period. Both statistical models yielded comparable estimates of glacier-wide average SWE (1% average difference at Gulkana, 4% average difference at Wolverine), although the spatial distributions produced by the models diverged in unsampled regions of the glacier, particularly at Wolverine. In total, six different methods for estimating the glacier-wide average agreed within ±11%. We assessed interannual variability in the spatial pattern of snow accumulation predicted by the statistical models using two quantitative metrics. Both glaciers exhibited a high degree of temporal stability, with ~85% of the glacier area experiencing less than 25% normalized absolute variability over this five-year interval. We found SWE at a sparse network (3 stakes per glacier) of long-term glaciological stake sites to be highly correlated with the GPR-derived glacier-wide average. We estimate that interannual variability in the spatial pattern of SWE is only a small component (4–10% of glacier-wide average) of the total mass balance uncertainty and thus, our findings support the concept that sparse stake networks effectively measure interannual variability in winter balance on glaciers, rather than some spatially varying pattern of snow accumulation.

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Short summary
Measuring the amount and spatial pattern of snow on glaciers is essential to monitoring glacier mass balance and quantifying the water budget of glacierized basins. Using repeat radar surveys for five consecutive years, we found that the spatial pattern in snow distribution is stable over the majority of the glacier and scales with the glacier-wide average. Our findings support the use of sparse stake networks for effectively measuring interannual variability in winter balance on glaciers.
Measuring the amount and spatial pattern of snow on glaciers is essential to monitoring glacier...
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