While climate change driven increase in air temperature has been correctly modeled in recent decades, the extent of its consequences is still uncertain. In high alpine environments, especially in steep rock walls, permafrost degradation reduces slope stability with critical consequences for people and infrastructures: to properly assess the risk, the rate of these changes must be monitored. In the last decades, electrical resistivity tomography (ERT) has been used in more than hundred studies to detect permafrost, but there are only limited long-term monitoring cases that mostly do not provide quantitative information. 

Here we compare ERT measurements from two alpine landforms with different altitude and lithology: Steintälli ridge (3160m asl, CH) and Mt. Zugspitze rock wall (2750 m asl, DE/AT). Standard procedures and permanently installed electrodes allow the collection of a unique dataset of consistent measurements since 2006. Supporting information like resistivity-temperature calibration from former studies, rock surface and borehole temperatures as well as active seismic refraction measurements enable an advanced quantitative interpretation of the results. 

Permafrost at both sites is close to disappearing and in both cases resistivity changes are evident and in good agreement with air temperature increase, although with different magnitudes according to the landform. The yearly 3D measurements of the Steintälli ridge show a sudden and conspicuous degradation (~40% of the volume in 15 years), while the monthly 2D monitoring of the north face of Mt. Zugspitze shows slow constant decrease in summer (~15% of the surface in 15 years) and a strong variation in winter in correlation with snow-height. 

For the first time we provide a quantification of alpine permafrost degradation rates in different landforms over 15 years. These datasets help to better understand the different characteristics of the thermal responses to the climate change induced stress on alpine permafrost environments.

How to cite: Scandroglio, R., Offer, M., and Krautblatter, M.: Long-time permafrost evolution in alpine bedrock: quantifying climate change effects with geoelectrical monitoring, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14390, https://doi.org/10.5194/egusphere-egu23-14390, 2023.

Although rock glaciers represent a common periglacial landform in the alpine environment, and have a significant contribution to the hydrological regime of the related areas, their hydrodynamic is relatively less defined if compared to moraines, talus, and hillslope deposits. So far, the hydraulic behaviour of frozen layers that may be found inside rock glaciers has been investigated only with geochemical analysis of their spring water. These previous studies observed that the frozen layer acts as an aquiclude (or aquitard) and separates a supra-permafrost flow component, originating from snow-ice melting and rainwater, and a deeper aquifer at the bottom of the rock glacier systems.

In this work we verified, for the first time with a geophysical monitoring method, the low-permeability hydraulic behaviour associated to the frozen layer of mountain permafrost subsoils. In the inactive rock glacier of Sadole Valley (Southern Alps, Trento Province, Italy) we performed an infiltration experiment combined with 2D electrical resistivity tomography (ERT) measurements in time-lapse configuration. Considering the same ERT transect, a time zero dataset (t₀) has been collected before the water injection, subsequently about 800 liters of salt water have been spilled (approximately in a point) on the surface of the rock glacier in the middle of the electrodes array, and 10 ERT datasets have been collected periodically in the following 24 hours. To highlight the variations of electrical resistivity in the frozen subsoil, related to the injected salt water flow, only the inverted resistivity model derived from t₀ dataset has been represented in terms of absolute resistivities, while the other time steps results have been evaluated in terms of percentage changes of resistivity with respect to the t₀ initial model.

Our results clearly agree with the assumption that a frozen layer acts as an aquiclude (or aquitard) in a mountain permafrost aquifer, since during the infiltration experiment the injected salt water was not able to infiltrate into the underlying permafrost layer. The positive outcome of this test, fronting impervious environment and logistic constraints, opens up interesting future scenarios regarding the application of this geophysical monitoring method for the hydraulic characterization of rock glaciers. The experiment, used in this work to evaluate the permeability of the frozen layer, could be adapted in future to evaluate (in a quantitative way) the hydraulic conductivity of the active layer in rock glacier aquifers.

How to cite: Pavoni, M., Boaga, J., Carrera, A., Zuecco, G., Carturan, L., and Zumiani, M.: Hydraulic behaviour of a mountain permafrost subsoil revealed by an infiltration experiment and ERT time-lapse measurements, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1137, https://doi.org/10.5194/egusphere-egu23-1137, 2023.

In many regions of the Northern Hemisphere, permafrost is thawing due to climate change. In steep terrain, this permafrost degradation can affect slope stability. In one of Iceland's eastern fjords, Seyðisfjörður, nine major landslide cycles have occurred in the last century, originating from the lower parts (< 500 m a.s.l.) of the Strandartindur slopes, with the largest landslide event ever recorded in Iceland occurring in December 2020. Its triggering mechanism is being intensively studied and its development is being monitored. In addition to these instabilities, slow movements are also observed in the upper part (> 500 - 1010 m a.s.l.) of these slopes. In these upper areas, it is not known whether permafrost is present in the subsurface or what is causing it to creep downward. To further investigate the stability of these slopes, it is important to know and map the distribution and condition of possible permafrost layers. Therefore, electrical resistivity tomography (ERT) and ground penetrating radar (GPR) measurements were performed to study the presence and distribution of permafrost in the mountain, Strandartindur, above Seyðisfjörður. A combination of measurements is used as ERT responds primarily to the electrical resistivity of the subsurface, but this can depend strongly on other factors such as porosity, water content, etc., and GPR can help map the presence of different interfaces in the soil determined by their different physical properties, such as relative electrical permittivity, but also conductivity, which is the reciprocal of resistivity. Combining the two methods allows us to get a clearer picture of the subsurface. As a benchmark for ERT measurements in the field, a laboratory setup was performed with soil and rock samples at different temperatures and water saturations to study the behavior of frozen and non-frozen conditions in our geologic environment. With all of these measurements, we aim to answer the questions of whether permafrost is present in the selected area, what the distribution of permafrost is, whether we can use laboratory ERT to establish reference resistivity values, and if these methods are appropriate for this area.

How to cite: von der Esch, A., Piispa, E. J., and Sæmundsson, Þ.: Electrical Resistivity Tomography and Ground-Penetrating Radar Measurements for Permafrost Detection on a Mountain Slope at Strandartindur, Seyðisfjörður - East Iceland, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4135, https://doi.org/10.5194/egusphere-egu23-4135, 2023.

Cold regions are increasingly subjected to higher air temperatures, causing warming of permafrost and a deepening of the active layer. This activates hydrogeological groundwater flow and new groundwater pathways to emerge. Monitoring of the active layer depth occurs mainly with the use of temperature observations, but a more flexible and non-invasive method to study transient subsurface processes is with the use of Electrical Resistivity Tomography (ERT) observations. 

Automated time-laps ERT arrays are used to monitor the frozen ground evolution during various seasons, observing resistivity variations during freezing and thawing. Similarly, the leaching of meltwater into the ground under freezing/thawing conditions can be observed. Not only geophysical changes such as fluctuations in water content and water table, but also temperature variations affect the electrical resistivity field. In order to track the development of permafrost active-layer freeze-thaw fronts using ERT observations, it is thus essential that the effect of temperature on the resistivity is clearly defined at realistic scales representing field conditions. Our aim is to determine fluid resistivity at various stages during freezing and thawing and validate current temperature–resistivity relations for partly frozen soils.

This study used a soil column (0.4 m diameter, 1 m heigh) equipped with 96 stainless steel electrodes placed at 8 horizontal rings of 12 electrodes each at various heights around the circumference of the column alongside with temperature sensors. The column was fully insulated on the sides and top except for the bottom, creating a 1D heat transfer system. The soil column was filled with quartzite sand with a D50 of 350 (μm) and organic matter content of 5 (wgt %). The experimental setup was placed within a climate chamber where the column was frozen to -4 °C and thawed to 3 °C over a 3-month period. During the freezing and thawing phase, a full 3D resistivity image was collected using the ERT at a weekly interval. Initial results show that the setup is capable of simulating permafrost freezing and thawing dynamics and ongoing work focuses on the relation between the temperature and time lapse ERT resistivity observations.

How to cite: de Bruin, J., Bense, V., and van der Ploeg, M.: Detecting permafrost freeze-thaw front propagation using time-laps ERT observations in a large column experiment, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4895, https://doi.org/10.5194/egusphere-egu23-4895, 2023.

Permafrost peatlands are highly vulnerable ecosystems in a warming climate; their thaw greatly impacts carbon storage capacity and endangers existing landscape morphology. Due to their remoteness and, in some cases, protected status, it is difficult to characterise and monitor the subsurface using invasive methods. Geophysical investigations are useful in such cases allowing relatively rapid and extensive subsurface mapping. We focus here on the emerging high-frequency induced polarisation (HFIP) method, which can be effective in permafrost hydrology research as the geoelectrical properties of frozen water display a characteristic frequency-dependence between ranges of 100 Hz and 100 kHz.

HFIP field measurements were conducted using the Chameleon-II equipment (Radic Research) on two peat permafrost sites located in Abisko, Northern Sweden: Storflaket mire and Heliport mire. The sites have been subject to routine permafrost monitoring since 1978 and are known to have an upper peat layer underlain by a silt-rich subsoil. We present the results of 2D surveys measuring frequencies ranging from 1 Hz to 57 kHz, which capture a high-frequency phase shift peak. Field data are inverted for each measured frequency separately with ResIPy, using an appropriate data error quantification model. The spectral data analysis captures heterogeneity within the subsurface, i.e., layered medium, permafrost mire boundary and ice-rich versus ice-poor regions. Identification of spectrally distinct regions allows the application of an appropriate relaxation model. For this study, we apply a two-component mixture model for ice-content estimation. Our results extend the existing knowledge at this site by quantifying ice content in a 2D plane, thus improving the foundation for further modelling studies.

How to cite: Sugand, M. G., Hördt, A., and Binley, A.: Resolving ice content heterogeneity within permafrost peatlands using high-frequency induced polarisation., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16522, https://doi.org/10.5194/egusphere-egu23-16522, 2023.

We have developed a drone-based GPR system at the University of Lausanne that allows for the safe and efficient acquisition of large, high-density, 3D and 4D datasets over alpine glaciers. The system is able to record approximately 4 line-km of high-quality GPR data per set of drone batteries in less than 30 minutes of operation which, combined with multiple sets of batteries and/or the possibility of charging at the field site, means that 3D datasets over a large area can be acquired with unprecedented efficiency. The latter performance is possible thanks to (i) a custom-made real-time-sampling GPR controller that has been specifically designed for glaciers studies, (ii) minimization of the total payload weight using custom-built antennas and carbon-fiber components, and (iii) development of an optimized survey methodology. Further, because the drone is equipped with real-time kinematic GPS positioning, survey paths can be repeated with great precision, which opens new opportunities in term of 4D data acquisitions.

In the summer of 2022, we acquired both 3D and 4D data over two Swiss glaciers. On the Otemma glacier, we surveyed a grid of 462 profiles representing a total length of 112 line-km of data in only four days. After 3D binning, the trace spacing intervals in the in-line and crossline directions were respectively 0.4 m and 1 m, making this arguably the largest 3D GPR dataset of such density ever recorded over ice. The interface between the ice and the bedrock, visible on all profiles, extends to 1000 ns which translates into a depth of approximately 80 m. In addition, internal englacial and subglacial 3D structures are clearly detectable.

In parallel, we visited the Rhône glacier on a monthly basis between June and September 2022. A collapse feature, identified by the presence of large circular crevasses, had formed and was evolving close to the snout of the glacier. This represented a great opportunity to test the 4D acquisition capabilities of our system. We collected four high-density 3D datasets on the same survey grid. The repeatability of the trajectories was excellent as the paths differ only by a few centimeters between occurrences. Clear variations in the internal structure of the glacier are visible which will be investigated in the upcoming months.

How to cite: Ruols, B., Baron, L., and Irving, J.: High-density 3D and 4D GPR data acquisitions over alpine glaciers using a newly developed drone-based system., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9619, https://doi.org/10.5194/egusphere-egu23-9619, 2023.

Since 2012 we monitor avalanche activity using distributed acoustic and seismic fiber optic sensing at our avalanche test area at Lech am Arlberg, Austria. The method is based on an optical time domain reflectometer system that detects seismic vibrations and acoustic signals on a fiber optic cable that can have a length of up to 30 km in 80 cm resolution. While in the first years we focused on successfully developing an operational avalanche detection system that is able to tell in real time reliably when an avalanche was triggered and what the size of the avalanche is, we now present our investigations of the seismic signals to measure snow properties such as snow depth and avalanche properties such as flow behavior. Our test in winter 2022 recorded by blasting triggered avalanches and during data post processing we extracted seismic guided waves. We discuss methods for extracting information from guided waves for measuring snow depth, which was verified against spatial snow depth measurements from terrestrial laser scanning. Analyzing the seismic signals of avalanches with run-out distances ranging from a few metres to approximately 250 m allows us to differentiate between wet and snow avalanches, which is discussed in the context of avalanche dynamics.

How to cite: Prokop, A., Agostinetti, N. P., and Graseman, B.: Measuring snow and avalanche properties using acoustic and seismic distributed fiber optic sensing, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5851, https://doi.org/10.5194/egusphere-egu23-5851, 2023.

Snow microstructure defines the physical, mechanical and electromagnetic properties of snow. Accurate information of snow structure is needed by many applications, including avalanche forecasting (Hirashima et al., 2008) and numerical weather prediction (de Rosnay et al., 2014). The interaction of electromagnetic waves with snow properties can be applied in satellite remote sensing to retrieve, for example, global information of snow mass (Pulliainen et al., 2020). Objective in-situ observations of snow microstructure are needed to validate and develop both physical models and satellite snow retrieval algorithms. Conventional measurements of snow grain size are unsatisfactory in this regard, as the parameter is difficult to measure objectively, and even its definition is ambiguous (Mätzler, 2002). Hence, recent efforts have focused on developing forward models of microwave interactions and snow specific surface area (SSA), which can be objectively measured in field and laboratory conditions using various methods. A recently proposed approach links SSA to microwave scattering properties through another physically defined parameter (Picard et al., 2022).

In the SnowAPP project, three field campaigns were carried out at the Finnish Meteorological Institute Arctic Research Centre in Sodankylä, with the goal of collecting data on snow microstructural properties and establishing the relation of microstructure to both optical reflectance and microwave emission and scattering from snow.  During the spring 2019 campaign, six different methods were used for measuring SSA; and several methods were used for measuring snow density, another important factor affecting especially the extinction of microwave energy. Furthermore, multi-frequency radiometry and a wide-band, high resolution spectrometer were used to measure microwave emission and reflectance. In this study, we compare objectively the SSA and density values obtained by the different methods in a round-robin exercise. The relation of measured snow microstructures to measured spectral properties of snow are discussed.

SnowAPP was funded by the Academy of Finland, with contributions from WSL Institute for Snow and Avalanche Research SLF, Centre Tecnològic de Telecomunicacions de Catalunya, Beijing Normal University, National Institute for Polar Research, Meteorological Research Institute (Japan), and Université Grenoble Alpes.

de Rosnay, P., Balsamo, G., Albergel, C., Muñoz-Sabater, J., & Isaksen, L. (2014). Initialisation of land surface variables for numerical weather prediction. Surveys in Geophysics, 35(3), 607–621. https://doi.org/10.1007/s10712-012-9207-x

Hirashima, H., Nishimura, K., Yamaguchi, S., Sato, A., & Lehning, M. (2008). Avalanche forecasting in a heavy snowfall area using the snowpack model. Cold Regions Science and Technology, 51(2–3), 191–203. https://doi.org/10.1016/j.coldregions.2007.05.013

Mätzler, C., 2002. Relation between grain-size and correlation length of snow. J. Glaciol., (48)162: 461-466.

Picard, G., Löwe, H., Domine, F., Arnaud, L., Larue, F., Favier, V., & Meur, E. le. (2022). The Microwave Snow Grain Size: A New Concept to Predict Satellite Observations Over Snow-Covered Regions. https://doi.org/10.1029/2021AV000630

Pulliainen, J., Luojus, K., Derksen, C., Mudryk, L., Lemmetyinen, J., Salminen, M., Ikonen, J., Takala, M., Cohen, J., Smolander, T., & Norberg, J. (2020). Patterns and trends of Northern Hemisphere snow mass from 1980 to 2018. Nature, 581(7808), 294–298. https://doi.org/10.1038/s41586-020-2258-0

How to cite: Kontu, A., Leppänen, L., Pirazzini, R., Hannula, H.-R., Lemmetyinen, J., Räisänen, P., McFarlane, A., Espin Lopez, P., Anttila, K., Rimali, A., Suokanerva, H., Yang, J., Aoki, T., Niwano, M., Picard, G., Ollivier, I., Arnaud, L., Matzl, M., Merkouriad, I., and Schneebeli, M.: Intercomparison of quantification methods for snow microstructure during the SnowAPP experiment, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16342, https://doi.org/10.5194/egusphere-egu23-16342, 2023.

Many of the gauged snow depth measurements in the European Alps began in the late 19th and early 20th centuries. We leverage this reasonably long period of record to investigate the historical sensitivity of snow depths as a function of precipitation, mean temperature, and elevation. By controlling for changes in precipitation, we can isolate the influence that different temperature changes have on snow depths at varying elevation bands. This simple, yet effective, approach to defining our historical sensitivity can provide a robust observational framework to evaluate the impact that a range of different future warming scenarios would have on snow depths across the Alps. As a result, adaptation and mitigation measures can be put in place for a variety of end users, such as ski tourism and water resource management. Furthermore, this provides an observational reference by which to evaluate the performance of climate model simulations.

How to cite: Switanek, M., Schöner, W., and Resch, G.: Snow depth sensitivity to mean temperature and elevation in the European Alps, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13127, https://doi.org/10.5194/egusphere-egu23-13127, 2023.

Monitoring of the thickness and elastic parameters of floating ice on lakes and the sea is of interest in understanding the climate change impact on Alpine and Arctic environments, assessing ice safety for recreational and engineering purposes, studying ice shelves as well as exploring possibilities for the future exploration of the icy crusts of ocean worlds in our solar system. A multitude of geophysical methods exist today to monitor sea and lake ice thickness as well as elastic parameters. Mostly, seismic and radar measurements are used. Both methods have in common that they come with significant logistical effort and expensive equipment. In this study, we present a novel low cost approach using acoustic sensors for ice monitoring.

We explored the possibility of using microphones deployed on frozen lakes in the Swiss Alps to monitor the lake ice-thickness using acoustic signals originating from frequently occurring ice quakes. Data were obtained during a three-month-long field campaign at Lake St. Moritz in Switzerland in winter 2021/2022. Three microphone stations were placed on the lake in addition to five conventional seismometers. These seismometers were used to compare the acoustic signals with the seismic ice quake recordings. Additionally, also active-source experiments were conducted using hammer strokes as source, which were used to constrain elastic parameters of the ice.

The acoustic recordings of ice quakes allowed us to exploit the unique characteristics of so-called air-coupled waves to determine time-dependent ice thickness curves of Lake St. Moritz for winter 2021/2022 using acoustic data only. Furthermore, the acoustic data allowed us to gain new insights into the ice/air coupling of seismic waves in ice. 

How to cite: Wetter, C., Schmelzbach, C., and Stähler, S. C.: Monitoring lake ice with acoustic sensors, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10127, https://doi.org/10.5194/egusphere-egu23-10127, 2023.

We present maps of the sub-ice platelet layer (SIPL) thickness and ice volume fraction beneath the land-fast sea ice in Atka Bay adjacent to the Ekström Ice Shelf (southeastern Weddell Sea, Antarctica). The widespread SIPL beneath Antarctic fast ice is indicative of basal melt of nearby ice shelves, contributes to the sea ice mass balance and provides a unique ecological habitat. Where plumes of supercooled Ice Shelf Water (ISW) rise to the surface rapid formation of platelet ice can lead to the presence of a semi-consolidated SIPL beneath consolidated fast ice.

Here we present data from extensive electromagnetic (EM) induction surveying with the multi-frequency EM sounder GEM-2 between May and December, 2022. It includes monthly survey data along a fixed transect line across Atka Bay between May and October, as well as comprehensive mapping across the entire bay in November and December. The GEM-2 surveys were supplemented by drill hole thickness measurements, ice coring and CTD profiles. A new data processing and inversion scheme was successfully applied to over 1000 km of EM profiles with a horizontal resolution of one meter. We obtained layer thicknesses of the consolidated ice plus snow layer, the SIPL, and the respective layer conductivities. The latter were used to derive SIPL ice volume fraction and an indicator for flooding at the snow-ice interface. The robustness of the method was validated by drill hole transects and CTD profiles.

Our results support conclusions about the spatial variability of the ocean heat flux linked to outflow of ISW from beneath the ice shelf cavity. Temporally, we found that the end of SIPL growth and the onset of its thinning in summer can be linked to the disappearance of supercooled water in the upper water column.

How to cite: Neudert, M., Arndt, S., Schulze, M., Hendricks, S., and Haas, C.: High resolution maps of the sub-ice platelet layer in Atka Bay from electromagnetic induction sounding, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5545, https://doi.org/10.5194/egusphere-egu23-5545, 2023.

Seismic surveys are widely used to characterise the properties of glaciers, their basal material and conditions, and ice dynamics. The emerging technology of Distributed Acoustic Sensing (DAS) uses fibre optic cables as seismic sensors, allowing observations to be made at higher spatial resolution than possible using traditional geophone deployments. Passive DAS surveys generate large data volumes from which the rate of occurrence and failure mechanism of ice quakes can be constrained, but such large datasets are computationally expensive and time consuming to analyse. Machine learning tools can provide an effective means of automatically identifying seismic events within the data set, avoiding a bottleneck in the data analysis process.

Here, we present a novel approach to machine learning for a borehole-deployed DAS system on Store Glacier, West Greenland. Data were acquired in July 2019, as part of the RESPONDER project, using a Silixa iDAS interrogator and a BRUsens fibre optic cable installed in a 1043 m-deep borehole. The data set includes controlled-source vertical seismic profiles (VSPs) and a 3-day passive record of cryoseismicity.  To identify seismic events in this record, we used a convolutional neural network (CNN). A CNN is a deep learning algorithm and a powerful classification tool, widely applied to the analysis of images and time series data, i.e. to recognise seismic phases for long-range earthquake detection.

For the Store Glacier data set, a CNN was trained on hand-labelled, uniformly-sized time-windows of data, focusing initially on the high-signal-to-noise-ratio seismic arrivals in the VSPs. The trained CNN achieved an accuracy of 90% in recognising seismic energy in new windows. However, the computational time taken for training proved impractical. Training a CNN instead to identify events in the frequency-wavenumber (f-k) domain both reduced the size of each data sample by a factor of 340, yet still provided accurate classification. This decrease in input data volume yields a dramatic decrease in the time required for detection. The CNN required only 1.2 s, with an additional 5.6 s to implement the f-k transform, to process 30 s of data, compared with 129 s to process the same data in the time domain. This suggests that f-k approaches have potential for real-time DAS applications.

Continuing analysis will assess the temporal distribution of passively recorded seismicity over the 3 days of data. Beyond this current phase of work, estimated source locations and focal mechanisms of detected events could be used to provide information on basal conditions, internal deformation and crevasse formation. These new seismic observations will help further constrain the ice dynamics and hydrological properties of Store Glacier that have been observed in previous studies of the area.

The efficiency of training a CNN for event identification in the f-k domain allows detailed insight to be made into the origins and style of glacier seismicity, facilitating further development to passive DAS instrumentation and its applications.

How to cite: Pretorius, A., Booth, A., Smith, E., Nowacki, A., de Ridder, S., Christoffersen, P., and Hubbard, B.: Efficient neural network-based detection of seismicity in fibre optic data from Store Glacier, West Greenland, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-93, https://doi.org/10.5194/egusphere-egu23-93, 2023.

On the Greenland Ice Sheet, the firn layer holds the potential to trap and refreeze surface meltwater within its pore space. Acting as a buffer, it prevents meltwater from leaving the ice sheet. However, several meter-thick ice slabs have developed in the firn during the last two decades, reducing subsurface permeability and inhibiting vertical meltwater percolation. Ice slabs are located above the long-term equilibrium line along the west, north and northeast coasts of the ice sheet. Through time, ice slabs have thickened while new ones have developed at higher elevations. Concomitantly, the area of the ice sheet drained by surface rivers has increased by 29% from 1985 to 2020. Nowadays, 5-10% of surface losses through meltwater runoff originates from these newly drained areas, which correspond strongly with where ice slabs are located.

Here, we demonstrate that the highest elevation which is drained by surface rivers – termed the maximum visible runoff limit – is controlled by the ice content in the subsurface firn. Using ice slab thickness derived from the accumulation radar and annual maximum visible limit retrievals from Landsat imagery from 2002 to 2018, we show that a sub-surface ice content threshold triggers the shift from a ‘firn deep percolation regime’ to a ‘firn runoff regime’. Although ice slabs act as an aquitard, vertical meltwater percolation can still take place where visible meltwater ponds at the surface. We show that once the firn runoff regime is underway, ice slabs are thicker in locations with active surface hydrology compared to locations where no meltwater is visible at the surface. Spatial heterogeneity in ice slab thickness is therefore predominantly controlled by surface hydrology features.

How to cite: Jullien, N., Tedstone, A., and Machguth, H.: Ice slab thickening drives surface runoff expansion from the Greenland Ice Sheet’s percolation zone - and vice versa, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2250, https://doi.org/10.5194/egusphere-egu23-2250, 2023.

The short observational record is one of the main obstacles to improving the present understanding of the future of the Polar ice sheets. While the quantity and quality of observations presently are increasing observations from before the 1990s are scarce. Here, we present the first results from a newly digitized ice-penetrating radar dataset acquired over the Greenland Ice Sheet in the 1970s. The data consist of more than 170,000 km of radar flight lines. While the ice thickness information from the data has been digitized by previous studies, the data itself (notably the z-scopes) were until recently only available as 35-mm films, microfiche copies of the films, and enlarged positives: Formats that are not usable for digital analysis.

In 2019, the film rolls were scanned by a digital scanner and subsequently, a large effort has been directed at carrying out quality control of the data with the view of making them publicly available.  Here we present the first results from this digitization. The overall data quality is good, and we are able to retrieve valuable information on layer stratigraphy and ice-flow dynamics.

How to cite: Karlsson, N. B., Schroeder, D., Sørensen, L. S., Chu, W., Teisberg, T., Tarzano, A., Skou, N., and Dall, J.: A new view of a 1970s radar dataset from Greenland, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6935, https://doi.org/10.5194/egusphere-egu23-6935, 2023.

Anisotropic crystal fabrics in ice sheets develop as a consequence of deformation and hence record information of past ice flow. Simultaneously, the fabric affects the present-day bulk mechanical properties of glacier ice because the susceptibility of ice crystals to deformation is highly anisotropic. This is particularly relevant in dynamic areas such as fast-flowing glaciers and ice streams, where the formation of strong fabrics might play a critical role in facilitating ice flow. Anisotropy is ignored in most state-of-the-art ice sheet models, and while its importance has long been recognized, accounting for fabric evolution and its impact on the ice viscosity has only recently become feasible. Both the application of such models to ice streams and their verification through in-situ observations are still rare. We present an extensive dataset of fabric anisotropy derived from ground-based and air-borne radar data, covering approximately 24,000 km² of the Northeast Greenland Ice Stream onset region. Our methods yield the horizontal anisotropy and are based on travel time anisotropy as well as birefringence-induced power modulation of radar signals. These methods complement each other and show good agreement. We compare the in-situ observations with the results obtained from a fabric-evolution model employed along flow line bundles in the ice stream onset to discuss the fabric in light of past flow history and its significance for the current flow mechanics of the ice stream.

How to cite: Gerber, T. and Eisen, O. and the NEGIS community: Spatial variation of ice crystal fabric and implications of anisotropic flow in the Northeast Greenland Ice Stream, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7695, https://doi.org/10.5194/egusphere-egu23-7695, 2023.

We use cross-correlations of ambient seismic noise data between pairs of 9 broadband three component seismometers to investigate variations in velocity structure and anisotropy in the vicinity of the EastGRIP camp along and across flow of the Northeast Greenland Ice Stream (NEGIS).

From the 9-component correlation tensors associated with all station pairs we derive dispersion curves of Rayleigh and Love wave group velocities between station pairs at frequencies from 1 to 25 Hz. The distributions of the Rayleigh and Love group velocities exhibit anisotropy variations for the along and across flow component. To better assess those variations, we invert the dispersions curves to shear wave velocities in the horizontal (Vsh) and vertical (Vsv) direction for the top 300 m of the NEGIS using a Markov Chain Monte Carlo approach.

The reconstructed 1-D shear velocity model revels radial anisotropy in the NEGIS. Along and across flow vertical shear wave velocities (Vsv) identify comparable velocity profiles for all depths. However, horizontal shear wave velocities (Vsh) are faster by approximately 250 m/s in the along flow direction below a depth of 100 m, i.e. below the firn-ice transition.

This type of anisotropy seems to arise from the alignment of a crystallographic preferred orientation, due to deformation associated with shear zones. The role of anisotropy as e.g. created by air bubbles in the firn and ice matrix, is yet unclear.

Faster Vsh velocities in the along flow direction support that the NEGIS has crystal orientation alignment normal to the plane of shear compression (i.e. ice crystals orientated across flow) within the upper 300 m of the ice stream and are in alignment with the results from other methods. We demonstrate that simple, short duration (2-3 weeks), passive seismic deployment and environmental noise-based analysis can be used to determine the anisotropy of the upper part of ice masses.

How to cite: Pearce, E., Zigone, D., Schoonman, C., Franke, S., Eisen, O., and Rimpot, J.: Investigating firn and ice anisotropy around the EastGRIP Camp, North East Greenland Ice Stream, from ambient noise surface waves, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-40, https://doi.org/10.5194/egusphere-egu23-40, 2023.

The ice mass balance of Antarctica has been steadily and strongly decreasing over recent decades, with major ramifications for global sea levels. Satellite remote sensing offers global, daily coverage of ice mass changes, which is essential for understanding land ice changes and their effects on global climate. However, we need to correct for processes including firn densification, glacial isostatic adjustment, elastic compensation of the Earth’s surface, ocean tides, and inverse barometer effect. Of these corrections, understanding the changes to the firn layer constitutes one of the largest uncertainties in making estimates of the surface mass balance from space. Furthermore, the development of firn models that aid our understanding of firn densification processes is hampered by a lack of observations.

Radar sounder reflections contain information about the roughness and permittivity of the reflecting interface, allowing us to map the spatial variability of the ice surface characteristics. In 2022, a helicopter-mounted ice-penetrating radar system developed by the University of Texas Institute for Geophysics collected high-quality radar observations over the Dotson Ice Shelf, West Antarctica. These surveys obtained clearly defined surface and bed reflections. We derived near-surface density along these survey flight lines using the radar statistical reconnaissance method developed by Grima, 2014. We calibrated our estimates with contemporary observations, including ground penetrating radar, a shallow ice core, an Autonomous phase-sensitive Radio Echo-sounder (ApRES), and radar soundings of well-defined surfaces from a calibration flight.

How to cite: Eayrs, C., Beem, L., Lee, C.-K., Lee, W. S., Chung, J., Pierce, C., Stutz, J., and Holland, D.: Variability of surface density at Dotson Ice Shelf, West Antarctica, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-952, https://doi.org/10.5194/egusphere-egu23-952, 2023.

How to cite: Smith, E. C., Karplus, M., Walter, J., Nakata, N., Booth, A. D., Gonzalez, L., Pretorius, A., Agnew, R., Veitch, S., Dawson, E. J., May, D., Summers, P., Young, T. J., Christoffersen, P., and Tulaczyk, S.: Thwaites Glacier Eastern Shear Margin: Insights from two broadband seismic arrays, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16308, https://doi.org/10.5194/egusphere-egu23-16308, 2023.

The climatic conditions over ice sheets at the time of snow deposition and compaction imprint distinctive crystallographic properties to the resulting ice. As it gets buried, its macroscopic structure evolves due to vertical compression but retains traces of the climatic imprint that generate distinctive mechanical, thermal and optical properties. Because climate alternates between glacial periods, that are colder and dustier, and interglacial periods, the ice sheets are composed from layers with alternating mechanical properties. Here we compare ice core dust content, crystal orientation fabrics and englacial vertical strain-rates, measured with a phase-sensitive radar (ApRES), at the South Pole and EPICA Dome C ice cores. In agreement with previous observations, we show that ice deposited during glacial periods develops stronger crystal orientation fabrics. In addition, we show that ice deposited during glacial periods is harder in vertical compression and horizontal extension, up to about three times, but softer in shear. These variations in mechanical properties are ignored in ice-flow models but they could be critical for the interpretation of ice core records. Also, we show that the changes in crystal orientation fabrics due to transitions from interglacial to glacial conditions can be detected by radar. This information can be used to constrain age-depth at future ice-core locations.

How to cite: Martin, C., Mulvaney, R., Conway, H., Koutnik, M., Stevens, C. M., Corr, H., Ritz, C., Nicholls, K., Drews, R., and Ershadi, M. R.: Climatic imprint in the mechanical properties of ice sheets and its effect on ice flow: Observations fromSouth Pole and EPICA Dome C ice cores, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7198, https://doi.org/10.5194/egusphere-egu23-7198, 2023.

Promontory ice rises are locally grounded features adjacent to ice shelves that are still connected to the ice sheet. Ice rises are an archive for the atmospheric and ice dynamic history of the respective outflow regions where the presence, absence, or migration of Raymond arches in radar stratigraphy represents a memory of the ice-rise evolution. However, ice rises and their inferred dynamic history are not yet used to constrain large-scale ice flow model spin-ups because matching the arch amplitudes includes many unknown parameters, e.g., those pertaining to ice rheology. In particular, anisotropic ice flow models predict gradients in ice fabric anisotropy on either side of an ice divide. However, this has thus far not been validated with observations.

The ground-based phase-sensitive Radio Echo Sounder (pRES) has previously been used to infer ice fabric types for various flow regimes using the co-polarized polarimetric coherence phase as a metric to extract information from the birefringent radar backscatter. Here, we apply this technique using quad-polarimetric radar data along a 5 km transect across a ridge near the triple junction of Hammarryggen Ice Rise at the Princess Ragnhild Coast. A comparison with ice core data collected at the dome shows that the magnitude of ice fabric anisotropy can reliably be reconstructed from the quad-polarimetric data. We use the combined dataset also to infer the spatial variation of ice fabric orientations in the vicinity of the triple junction. The observations are integrated with airborne radar profiles and strain rates based on the shallow ice approximation. We then discuss whether estimated anisotropy from radar polarimetry on ice rises, in general, can be another observational constraint to better ice rises as an archive of ice dynamics.

How to cite: Ershadi, M. R., Drews, R., Tsibulskaya, V., Sun, S., Henry, C., Oraschewski, F., Koch, I., Martin, C., Tison, J.-L., Wauthy, S., Bons, P., Eisen, O., and Pattyn, F.: Ice rise evolution derived from radar investigations at a promontory triple junction, Dronning Maud Land, East Antarctica, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8197, https://doi.org/10.5194/egusphere-egu23-8197, 2023.

The Whillans Ice Stream (WIS) is a major outlet of the West Antarctic Ice Sheet. Significantly, the downstream portion of the WIS is presently decelerating, possibly stagnating by the end of this century. Additionally, this downstream region of WIS is unique in that it moves primarily by stick-slip motion. However, both the rate of deceleration as well as the percent of motion accommodated by stick-slip motion is spatially variable. Such spatial variability is potentially linked to associated variability in basal conditions. Active source seismic measurement are capable of providing high-resolution insights into basal conditions, however, they are time-consuming to collect, limiting the spatial extent over which they can be acquired. In this presentation, we will use passive seismic measurements collected at over 50 seismic stations to map sediment thickness and ice-bed conditions across the region. This will be done using the receiver function method which images the depth and physical properties of sediments by modeling the arrival times and amplitudes of seismic waves that interact with subglacial sedimentary structures. We will first map conditions at the ice-bed interface by using relatively high-frequency waveforms (> 2 Hz) as they are sensitive to the physical properties of the shallow (< 20m ) subglacial sediments layers. Across the entirety of the study region, we find that this uppermost layer of sediments is characterized by relatively high porosity sediments.  Second, we will utilize lower frequencies (< 2 Hz) to map the depth basement, finding that the entire region is underlain 100’s of meters of sediments (Gustafson et al., Science, 2022). We will use our maps of sediment properties and thickness to investigate potential mechanisms for the observed variability in deceleration and stick-slip behavior of the WIS.  

How to cite: Winberry, J. P.: Basal Conditions and Sedimentary Structure of the Whillans Ice Stream., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9621, https://doi.org/10.5194/egusphere-egu23-9621, 2023.