CR6.2

Debris cover on glaciers is an important component of glacial systems as it influences climate-glacier dynamics and thus the lifespan of glaciers. Increasing air temperatures, permafrost thaw, as well as rock faces freshly exposed by glacier downwasting results in increased rockfall activity and debris input into the glacier system. In the ablation zone, negative mass balances result in an enhanced melt-out of englacial debris to the glacier system. Glacier debris cover thus represents a signal of climate warming in mountain areas. To assess the temporal development of debris on glaciers of the Eastern Alps, Austria, we mapped debris cover on 255 of the more than 800 glaciers using Landsat data at three time steps between 1996 and 2015. We applied a ratio-based threshold classification technique using existing glacier outlines. The debris cover evolution was subsequently compared to glacier changes. Glacier and glacier catchment characteristics have been analysed using GIS techniques and statistics in order to investigate potential reasons for debris cover change.

Across the Austrian Alps debris cover increased by more than 10% between 1996 and 2015 while glaciers retreated significantly in response to climate warming. Debris cover distribution shows regional variability with some mountain ranges being characterised by mean debris cover on glaciers of up to 75%. We also observed a general rise of mean elevation of debris cover on glaciers in Austria. Debris cover distribution and dynamics are highly variable due to topographic, lithological and structural settings that determine the amount of debris delivered to and stored in the glacier system. Lower relative debris cover is observed on glaciers with higher mean and maximum elevation. Additionally, glaciers with increased mean slope, as well as catchments with large areas of steep slopes and a high elevation range of these slopes tend to show higher debris cover. Both parameters indicate that the influence of the steep rockwalls in the glacier catchment is a first order control on debris cover at regional scale. We can also show that catchments with a high percentage of potential permafrost distribution contain glaciers with a higher relative debris cover.

Despite strong variation in debris cover, all glaciers investigated melted at increasing rates. We conclude that the retarding effects of debris cover on the mass balance and melt rate of Austrian glaciers is strongly subdued compared to other mountain areas. The study indicates that if this trend continues many glaciers in Austria may become fully debris covered in the future. However, since debris cover seems to have little impact on melt rates in the study area it will therefore not lead to a prolonged existence of debris-covered ice compared to clean ice glaciers.

How to cite: Otto, J.-C., Fleischer, F., Junker, R., and Hölbling, D.: Debris-cover on glaciers in the Austrian Alps. Regional patterns, Changes and Significance., EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-2036, https://doi.org/10.5194/egusphere-egu21-2036, 2021.

Many glaciers in High Mountain Asia are experiencing the debris-cover anomaly. The Kennicott Glacier, a large Alaskan Glacier, is also thinning most rapidly under debris cover. This contradiction has been explained by melt hotspots, such as ice cliffs, streams, or ponds scattered within the debris cover or by declining ice flow in time. We collected abundant in situ measurements of debris thickness, sub-debris melt, and ice cliff backwasting, allowing for extrapolation across the debris-covered tongue. A newly developed automatic ice cliff delineation method is the first to use only optical satellite imagery. The adaptive binary threshold method accurately estimates ice cliff coverage even where ice cliffs are small and debris color varies. We also develop additional remotely-sensed datasets of ice dynamical variables, other melt hot spots, and glacier thinning.

Kennicott Glacier exhibits the highest fractional area of ice cliffs (11.7 %) documented to date. Ice cliffs contribute 26 % of total melt across the glacier tongue. Although the relative importance of ice cliffs to area-average melt is significant, the absolute area-averaged melt is dominated by debris. At Kennicott Glacier, glacier-wide melt rates are not maximized in the zone of maximum thinning. Declining ice discharge through time therefore explains the rapid thinning. Through this study, Kennicott Glacier is the first glacier in Alaska, and the largest glacier globally, where melt across its debris-covered tongue has been rigorously quantified.

We also carefully explore the relationship between debris, melt hotspots, ice dynamics, and thinning across the debris-covered tongue. In doing so we reveal a chain of linked processes that can explain the striking patterns expressed on the debris-covered tongue of Kennicott Glacier.

How to cite: Anderson, L. S., Armstrong, W. H., Anderson, R. S., and Scherler, D.: Debris cover and the thinning of Kennicott Glacier, Alaska, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-15674, https://doi.org/10.5194/egusphere-egu21-15674, 2021.

We have modelled the influence of a supraglacial debris cover on the behavior of the Djankuat Glacier, a northwest-facing and partly debris-covered temperate valley glacier near the border of the Russian Federation and Georgia, which has been selected as a ‘reference glacier’ for the Caucasus region by the WGMS. A calibrated 1D coupled ice flow-mass balance-supraglacial debris cover model is used to assess the impact of the melt-altering effect of various supraglacial debris profiles on the overall steady state characteristics of the glacier. Additional experiments are also carried out to simulate the behavior of this specific debris-covered glacier in a warming future climate. The main results show that, when compared to its clean-ice version, the debris-covered version of the Djankuat Glacier exhibits longer but thinner ablation zones, accompanied by lower ice flow velocities, lower runoff production, as well as a dampening of the mass balance-elevation profile near the terminus. Experiments for warming climatic conditions primarily point out towards a significant delay of glacier retreat, as the dominant process for ice mass loss encompasses thinning out of the ablation zone. The above-mentioned effects are modelled to be increasingly pronounced with an increasing thickness and extent of the superimposed supraglacial debris cover.

How to cite: Verhaegen, Y., Rybak, O., Popovnin, V. V., and Huybrechts, P.: The influence of a supraglacial debris cover on the mass balance and dynamics of the Djankuat Glacier, Caucasus, Russian Federation, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-13641, https://doi.org/10.5194/egusphere-egu21-13641, 2021.

We have discovered and cored a massive ice mass buried underneath a meter of glacial debris in Ong Valley, Antarctica, which we report here to consist of two stacked ice bodies dated at >2 Ma. Glacial ice is known to be a great archive of atmospheric gasses, chemical compounds, and airborne particles. An ice mass of such antiquity, as reported here, may reveal information about our past which is otherwise unknown.

We determine the age of the ice directly by dating the dirt suspended within the ice and by dating the till layer covering the ice using cosmogenic nuclide: ¹⁰Be, ²⁶Al, and ²¹Ne. These cosmogenic nuclides are produced by cosmic-ray interactions with minerals near the Earth’s surface, and in this case in suspended dirt embedded in the ice. As the production rate of cosmogenic nuclides decreases rapidly with increasing depth below the Earth’s surface, the cosmogenic nuclide concentration profile yields information about the exposure history and further aid to constrain geological processes such as sublimation rates, and surface erosion rates. We further compare the cosmogenic nuclide model results with mapped glacial moraines adjacent to the current ice, and stable water isotope analysis throughout the core in order to explore the unique history that these two stacked ice masses have.

We find the uppermost section of this buried ice mass to be >2 Ma old. Large variation of cosmogenic nuclide concentrations downcore and stable water isotopes, suggests that the deepest section of the ice core may belong to a separate, older ice mass that has previously been exposed at the surface. Lateral moraines and measurements of cosmogenic nuclides in glacial debris further up valley suggest that this deeper, older ice may be >2.6 Ma old, and was most likely buried during glacial advancement into Ong Valley < 4 Ma ago.

How to cite: Bergelin, M., Putkonen, J., Balco, G., Morgan, D., Matheney, R. K., and Corbett, L. B.: Ancient Ice Buried Below a Meter of Regolith; Ong Valley, Antarctica, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-13872, https://doi.org/10.5194/egusphere-egu21-13872, 2021.

The melt rates of debris-covered glaciers in High Mountain Asia are highly heterogeneous and poorly constrained. Supraglacial cliffs are typical surface features of debris-covered glaciers and act as windows of energy transfer from the atmosphere to the ice, locally enhancing melt and mass losses of otherwise insulated ice. Despite this, their contribution to the glacier mass budget has never been quantified at the glacier scale.

Here we simulate the specific melt of all supraglacial ice cliffs individually in a Himalayan catchment (Langtang Valley, Nepalese Himalayas), using a process-based ice cliff melt model that has previously been validated in the catchment. Cliff outlines and initial topography are derived from high-resolution stereo SPOT6-imagery and the model is forced by meteorological data from on- and off-glacier automatic weather stations within the valley, both for the 2014 melt season. The model simulates ice cliff backwasting by considering the cliff-atmosphere energy-balance, reburial by debris and the effects of adjacent ponds. We estimate the contribution of ice cliffs to glacier surface mass balance derived from ensemble mean geodetic thinning observations and emergence flux calculations for the same glaciers 2006-2015.

We show that ice cliffs, although covering only 2.1 ±0.6 % of the debris-covered tongues, are partially responsible for the high thinning rates of debris-covered glacier tongues, leading to a catchment mass loss underestimation of 17 ±4 % if not considered. We show that cliffs enhance melt where other processes would suppress it, i.e. at high elevations or where debris is thick, and confirm that they contribute relatively more to glacier mass loss if oriented north.

Our approach bridges a scale gap in our understanding of the processes of debris-covered glacier mass losses, and a new quantification of their catchment wide melt and mass balance.

How to cite: Buri, P., Miles, E. S., Steiner, J., Ragettli, S., and Pellicciotti, F.: Modelling the contribution of ice cliff melt to glacier mass loss at the catchment scale, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-7026, https://doi.org/10.5194/egusphere-egu21-7026, 2021.

As glaciers in the Himalaya have lost mass, their proglacial lakes have expanded. Despite increasing interest in hazard assessment and mitigation of Glacial Lake Outburst Floods (GLOFs) over more than the last two decades, the role of glacier structures in controlling patterns and rates of glacier recession, and subsequently of lake expansion, have not yet been investigated in detail. This study aims to identify and map glacier structures over a 20-year period and investigate their significance in ice front recession. Four glacial lakes and their associated debris-covered glaciers have been examined in the Everest Region of Nepal and China: Imja Tsho, Tsho Rolpa, Lumdin Tsho, and Dang Pu Tsho. Lake area was mapped between 2000 and 2020 using images acquired from Landsat 5/7/8 and Sentinel 2. Discrete glacier flow units were identified and specific structures were digitised using the finest-resolution panchromatic bands. We reveal a distinct pattern of transverse features across each glacier that can be related to ice frontal position through time. While this is not the only controlling factor contributing towards ice front recession from lake-terminating glaciers in the Himalaya, it is clear that pre-existing structures influence the ice front shape and are involved in ice front deterioration. These observations could be used to indicate future ice front positions and behaviour, and rates of glacier recession and of lake expansion.  This would also enable GLOF hazard assessments to include more detailed glaciological factors and help in the recognition of such legacy structures in the behaviour of stagnant debris-covered ice masses that are part of terminal moraine complexes.

How to cite: Peacey, M., Holt, T., Glasser, N., and Reynolds, J.: Structural Controls on Himalayan Glacial Lake Expansion, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-7627, https://doi.org/10.5194/egusphere-egu21-7627, 2021.

Glaciers in High Mountain Asia (HMA) have been experiencing enhanced mass loss and velocity slowdown since the late 1990s, coincident with rising global and regional temperatures. In each HMA region with distinct climatic characteristics, the dynamical responses of glaciers vary substantially; yet these intra-regional variations are overlooked in regional assessments due to large-scale oversampling. In particular, the role of glacier morphological factors (e.g. size, elevation, hypsometry) in causing the different responses is poorly understood.

We investigated the velocity changes of the glaciers in three regions — the Eastern Himalaya, Spiti Lahaul, and Karakoram — between 2000 and 2016 in order to understand the key components of glacier sensitivity and their relationship with glacier morphology. Using the NASA Inter-Mission Time Series of Land Ice Velocity and Elevation dataset as input, we extracted glacier-specific velocities (and associated errors) using a bespoke MATLAB script, and compiled these into “mean annual velocity anomaly” series following established methods. Anomalies were analysed with glacier morphometric parameters using a linear regression approach, with statistically significant relationships identified.

Our results show that mean velocity anomaly within the Eastern Himalaya varies with glacier aspect, with mean annual anomalies of 0.09 ± 2.32 m yr^-1 per year for north-flowing glaciers and –0.1 ± 1.59 m yr^-1 per year for south-flowing glaciers. Glaciers in the Karakoram also show opposing trends, with anomalies of –0.86 ± 5.69 m yr^-1 per year and –3.23 ± 2.53 m yr^-1 per year in the north west, and 1.00 ± 3.80 m yr^-1 per year in the south east. Glacier slowdown in Spiti Lahaul is –0.37 ± 4.50 m yr^-1 per year, and we do not document contrasts in intra-regional glacier response. Overall, glacier size, minimum elevation and hypsometric integral are the most significantly correlated parameters to mean velocity anomaly. Percentage and area of debris, flow line length, slope and termination environment were also found to be important autocorrelations. Importantly, we find no consistent morphometric interactions contributing to glacier anomaly between all three regions, implying that glacier responses are unique and a cumulative product of their morphometric variability.

How to cite: Curry, C. S., Rowan, A. V., and Ng, F. S. L.: Exploring the causes of glacier velocity anomalies in High Mountain Asia: Analysis from the Karakoram, Spiti Lahaul and Eastern Himalaya, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-11907, https://doi.org/10.5194/egusphere-egu21-11907, 2021.

Debris thermal conductivity is a critical parameter in calculating a glacier’s sub-debris ice melt. The method widely used in publications to calculate apparent thermal conductivity of supraglacial debris layers is based on an estimate of volumetric heat capacity of the debris and simple heat diffusion principles and is presented in . The analysis of heat diffusion requires a vertical array of temperature measurements through the supraglacial debris cover. This study explores the effect of the temperature sampling interval on the thermal conductivity values derived using this method. Initial results indicate that the thermal diffusivity decreases linearly with an increasing sampling time from 30min to 6h by 0.2-0.4 mm²/s for glaciers in high mountain Asia during the monsoon season. These results suggest that care must be taken in choosing the analysis time interval for computing debris thermal conductivity and for comparing values between datasets sampled at different intervals. Current research aims to further investigate the cause of the artifact and determine how this problem can be solved. An open-source web application is therefore developed to help other scientists investigate the effect of the sampling interval on their calculated sub-debris ice melt. This study falls under the remit of the on debris-covered glaciers and is supported by data provided from within this group.

How to cite: Beck, C. and Nicholson, L.: Assessing the time-step dependency of calculating supraglacial debris thermal diffusivity from vertical temperature profiles, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-13402, https://doi.org/10.5194/egusphere-egu21-13402, 2021.

Over the past two decades, several semi-automated approaches for identifying debris covered ice have been proposed but challenges remain. Manual delineation of debris-covered glaciers has been recognized as an accurate method but is labor- and time-intensive for large regions. Geomorphological mapping in complex mountain environments is recognized as difficult and the accuracy of the associated maps is also highly dependent on the expertise of the mapper and their visual interpretation. Other methods seek to move beyond just optical or DEM-assisted classification to make use of the fact that there may be thermal differences in the temperature between debris-covered ice and the temperature of the surrounding non ice-cored zones, making it possible to identify debris-covered ice. Of course, with very thick debris cover, the signal of ice temperature will disappear, but this method may allow identification of zones that are ice cored that would otherwise be classed as non-glacier using other methods. In this study, we take advantage of thermal differences and near infrared measurements for both thin- and thick debris-covered ice that allows automated mapping of remote regions like Afghanistan. However, for debris-covered ice mapping, previous studies observed that using single thermal band misclassified the clean ice as debris-covered ice in transitional zones where clean ice and debris-covered ice meet, due to the coarser spatial resolution of available data (90 – 120 m). Therefore, this study investigated several Landsat 8 spectral bands with better spatial resolution to find correlation over debris-covered ice and to merge it with the thermal band. In a systematic test of all bands over the specific debris-covered ice, we determined that panchromatic band has significant reflectance on clean ice and debris-covered ice, from higher to lower value. Then, a new normalized index was developed accordingly, which increased the spatial resolution and improved the result. The Normalized Supraglacial Debris Index (NSDI) (eq. 1), has been tested for Afghanistan glaciers and validated through a fieldwork campaign on a specific glacier. For the test glacier, the method had 96% overall accuracy and a Kappa coefficient of 0.87.

  [1]

In addition we also tested the threshold values of NSDI based on the region of interest (ROI), and the ROI was selected up on five glaciers where the detailed map were available. During the process of mapping debris-covered ice using [1], we found several zones of likely debris-covered ice were not being detected with the threshold value neither with any near range. Then we performed a reflectance test up on each single band of Landsat 8 by classifying band value into equal classes of histograms, and found that SWIR has better reflectance in range of 6,230-7,160 values for the region where the debris-covered ice was missing. In addition the green band (B3) also had lower reflectance. Thus, in combination of both SWIR and Green bands we developed second index separately (eq. 2).

 [2]

In conclusion, the two newly developed indexes were abled to correctly map the debris covered ice with two different debris characteristics.

How to cite: Shokory, J. A. N. and Lane, S.: Automated debris-covered glacier mapping – development for and application to Afghanistan, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-9308, https://doi.org/10.5194/egusphere-egu21-9308, 2021.

Supraglacial debris covers 4% of mountain glacier area globally and generally reduces glacier surface melt. Studies have identified enhanced energy absorption at ice cliffs and supraglacial ponds scattered across the debris surface. Although these features generally cover a small portion of glacier surface area (5-10%) they contribute disproportionately to mass loss at the local glacier scales (20-40%). While past studies have identified their melt-enhancing role in High Mountain Asia, Alaska, and the Alps, it is not clear to what degree they enhance mass loss in other areas of the globe.

We model the surface energy balance for debris-covered ice, ice cliffs, and supraglacial ponds using meteorological records (4 radiative fluxes, wind speed, air temperature, humidity) from a set of on-glacier automated weather stations representing the global prevalence of debris covered glaciers. We generate 5000 random sets of values for physical parameters using probability distributions derived from literature. We also model the hypothetical energy balance of a debris-free glacier surface at each site, which we use to investigate the melt rates of distinct surface types relative to that of a clean ice glacier. This approach allows us to isolate the melt responses of debris, cliffs and ponds to the site specific meteorological forcing.

For each site we determine an Østrem curve for sub-debris melt as a function of debris thickness and a probabilistic understanding of surface energy absorption for ice cliffs, supraglacial ponds, and debris-covered ice. While debris leads to strong reductions in melt at all sites, we find an order-of-magnitude spread in sub-debris melt rates due solely to climatic differences between sites. The melt enhancement of ice cliffs relative to debris-covered ice is starkly apparent at all sites, and ice cliffs melt rates are generally 1.5-2.5 times the ablation rate for a clean ice surface. The supraglacial pond energy balance varies regionally, and is sensitive to wind speed and relative humidity, leading to energy absorption 0.4-1.2 times that of clean ice, but 5-10 times higher than debris-covered ice. Our results support the few past assessments of melt rates for cliffs and ponds, and indicate sub-regional coherence in the energy balance response of these features to climate.

How to cite: Miles, E., Steiner, J., Buri, P., Immerzeel, W., and Pellicciotti, F.: Global differences in the energy balance and melt rates of debris-covered glacier surfaces, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-10955, https://doi.org/10.5194/egusphere-egu21-10955, 2021.