Abstract
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 during the spring of 5 consecutive years. GPR
measurements showed steep snow water equivalent (SWE) elevation gradients at
both sites; continental Gulkana Glacier's SWE gradient averaged 115 mm 100 m−1 and maritime Wolverine Glacier's gradient averaged
440 mm 100 m−1 (over > 1000 m). 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 winter balance 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
5-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 winter SWE accumulation 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 temporally varying spatial pattern of snow accumulation.
Subject
Earth-Surface Processes,Water Science and Technology
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