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

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.

Multi-year evaluation of airborne geodetic surveys to estimate seasonal mass balance, Columbia and Rocky Mountains, Canada

“…Measurements of 1-year-old firn averaged 619 ± 47 kg m −3 (n = 8). Given the sustained mass loss of Pacific Northwest glaciers (Bolch et al, 2010;Menounos et al, 2019;Pelto, 2006), exposed firn is generally more than 1 year old, and we apply an uncertainty of 2 times the σ of our multi-year firn core observations (±15 %), which captures the range of observed firn densities (664-776 kg m −3 ). We use an ice density of 910 ± 10 kg m −3 (Clarke et al, 2013).…”

“…Random uncertainty stems from three sources that we assume to be independent: (i) elevation change uncertainty (σ h DEM ), (ii) glacier zone delineation uncertainty (σ A), and (iii) volume-to-mass density conversion uncertainty (σρ). We define σ h DEM following the methods detailed in Menounos et al (2019) and found an average decorrelation length of 0.75 km (Fig. S3).…”

“…Glaciers are in rapid retreat across western Canada (Menounos et al, 2019). Deglaciation is projected to have pronounced impacts on streamflow in western Canada (Clarke et al, 2015), with the greatest reductions in August and September streamflow as glaciers shrink (Huss and Hock, 2018;Jost et al, 2012).…”

Reanalysis of the US Geological Survey Benchmark Glaciers: long-term insight into climate forcing of glacier mass balance

“…At WG, ∼20 m amplitude drift and scour patterns characterize ∼20% of the accumulation zone ( Fig. 10a; McGrath and others, 2018). Safety and logistical practicalities prohibit the routine collection of a distributed set of measurements from this region, precluding an estimate of average mass within this region of extreme local variability.…”

“…For example, expanded measurement networks and GPR analyses at GG and WG suggest that the long-term measurements underestimate accumulation (McGrath and others, 2018). Yet the same expanded networks and the geodetic calibrations suggest that the historically sparse networks underestimate ablation.…”