A physically based 3‐D model of ice cliff evolution over debris‐covered glaciers

Abstract

We use high‐resolution digital elevation models (DEMs) from unmanned aerial vehicle (UAV) surveys to document the evolution of four ice cliffs on the debris‐covered tongue of Lirung Glacier, Nepal, over one ablation season. Observations show that out of four cliffs, three different patterns of evolution emerge: (i) reclining cliffs that flatten during the ablation season; (ii) stable cliffs that maintain a self‐similar geometry; and (iii) growing cliffs, expanding laterally. We use the insights from this unique data set to develop a 3‐D model of cliff backwasting and evolution that is validated against observations and an independent data set of volume losses. The model includes ablation at the cliff surface driven by energy exchange with the atmosphere, reburial of cliff cells by surrounding debris, and the effect of adjacent ponds. The cliff geometry is updated monthly to account for the modifications induced by each of those processes. Model results indicate that a major factor affecting the survival of steep cliffs is the coupling with ponded water at its base, which prevents progressive flattening and possible disappearance of a cliff. The radial growth observed at one cliff is explained by higher receipts of longwave and shortwave radiation, calculated taking into account atmospheric fluxes, shading, and the emission of longwave radiation from debris surfaces. The model is a clear step forward compared to existing static approaches that calculate atmospheric melt over an invariant cliff geometry and can be used for long‐term simulations of cliff evolution and to test existing hypotheses about cliffs' survival.

Pond Dynamics and Supraglacial-Englacial Connectivity on Debris-Covered Lirung Glacier, Nepal

“…Pond I (Figure 7) was also not observed in detail in May 2013, but appeared in the UAV orthophoto as a pond of moderate size (740 m 2 , which would possibly be observable by Landsat) with an adjacent ice cliff with a fairly uniform slope angle, and no vertical or overhanging face (Figure 7a-c; Cliff 4 in Brun et al, 2016;Buri et al, 2016). The pond shrank slightly in area to 550 m 2 by October 2013 (Figure 7), and the pond outline translated ∼10.5 m to the east (local glacier surface velocity is ∼3 m a −1 to the southeast).…”

Thickness estimation of supraglacial debris above ice cliff exposures using a high-resolution digital surface model derived from terrestrial photography

“…As ablation at ice cliffs is rapid, in the case of Ngozumpa glacier accounting for 40% of volume losses over the lower part of the glacier tongue (Thompson and others, 2016), repeat analysis of high-resolution photographic DSMs over time, that have been used to monitor ice cliff backwasting (e.g. Brun and others, 2016;Buri and others, 2016), would also reveal the spatial distribution of debris thickness behind the ice cliffs in the form of a time-space substitution. More extensive measurements of the underlying ice surface and debris thickness using high frequency GPR (McCarthy and others, 2017) offers a useful tool for determining relationships between surface terrain and underlying terrain that can be expected to offer valuable information in determining the validity of the assumption of horizontal extension of the debris/ ice interface applied in this study.…”

“…High-resolution photographic DSMs have already been generated for debris-covered glaciers and used to characterize the glacier surface (Kraaijenbrink and others, 2016), measure displacements of the glacier surface (Immerzeel and others, 2014) and monitor changes in ice cliffs (Brun and others, 2016;Buri and others, 2016). In this paper we (i) present a workflow to quantify debris thickness exposed above ice cliffs using measurements from scaled, high-resolution photographic DSMs, (ii) compare the derived debris thickness to available debris thickness collected by alternative means and (iii) discuss the utility and limitations of the new method of determining supraglacial debris thickness.…”

Automated detection of ice cliffs within supraglacial debris cover

“…The mechanism(s) of ice cliff formation, the controls of ice cliff migration patterns and ice cliff residence time on a glacier are gaining research attention but are still poorly understood processes, in part, due to a lack of base data (Reid and Brock, 2014;Watson et al, 2017). Melt and surface energy fluxes at specific ice cliffs have been studied in detail (Sakai et al, 1998;Han et al, 2010;Sakai et al, 2002;Reid and Brock, 2014;Buri et al, 2016a) and digital elevation model (DEM) differencing has shown the spatial trends of enhanced glacier melt relative to surrounding debris cover and ice cliff evolution at the scale of several cliffs or a single glacier tongue (Thompson et al, 2016;Brun et al, 2016). All of the studies mentioned suggest that ice cliffs, if present on a debris-covered glacier, need to be accounted for in order to adequately model glacier mass loss and response to climate.…”