Geophysical and in-situ measurements of the cryosphere offer important baseline datasets, as well as validation for modelling and remote sensing products. In this session we welcome contributions related to a wide spectrum of methods, including, but not limited to radioglaciology, active and passive seismology, acoustic sounding, Global Navigation Satellite System (GNSS) reflectometry or time delay techniques, cosmic ray neutron sensing, remotely operated vehicle (ROV) or drone applications, geoelectrics, nuclear magnetic resonance (NMR) and methods in radiative transfer (i.e. infrared photography, thermal sounding...).
Contributions could be related to field applications, new approaches in geophysical or in-situ survey techniques, or theoretical advances in data analysis processing or inversion. Case studies from all parts of the cryosphere such as snow and firn, alpine glaciers, ice sheets, glacial and periglacial environments, permafrost, or sea ice, are highly welcome. The focus of the session is to compare experiences in the application, processing, analysis and interpretation of different geophysical and in-situ techniques in these highly complex environments.
This year our session will be a virtual PICO session. The session begins with each presenter giving a “quick fire” 2-minute overview of their research, followed by breakout "rooms" - one per presentation, for authors to further discuss their research. We hope the virtual PICO format will provide as much lively discussion as our normal in-person PICO!
++++++++++++++++++++ Invited Speaker ++++++++++++++++++++
Amy R. Macfarlane: Quasi in-situ snow and sea ice interface microstructure measured by micro-computed tomography
IMPORTANT: THIS SESSION WILL NOW TAKE PLACE 1 HOUR LATER 16:30–18:00 CEST!
zoom link for this session
zoom link for this session
vPICO presentations: Mon, 26 Apr
The sea ice / snow interface in the high Arctic can no longer be thought of as simply black and white, but more complex than previously estimated. Our understanding of this interface is crucial for remote sensing, snow, brine and ice mass distribution, thermal conductivity and therefore ice growth and ice melt. To better understand the snow microstructure, we installed a micro-computed tomograph (micro-CT) in a cold laboratory on board Polarstern and measured a full annual cycle of the Arctic snow cover during the MOSAiC expedition. We discovered two large uncertainties when looking at the boundary between sea ice and snow boundary during the year.
1) Large temperature gradients of 100 K m-1 (compared to Alps (20 K m-1) specific to the high Arctic cause extreme metamorphism within the snowpack. This transports ice grains from the salty first year sea ice (FYI), across the interface up into the snowpack, producing snow with brine pockets on FYI. 10-30% of snow grains on FYI are affected by vapour migration from the sea ice, and can now be thought of as a mix of ocean and atmospheric sourced particles, which can be distinguished by oxygen isotope analysis. Brine in the snow structure has large implications for remote sensing backscatter and possibly mass balance.
2) Multi-year ice (MYI) also has large uncertainties, because the interface has a hard impenetrable layer- because of the porous summer ice surface, known as the surface scattering layer (SSL) after refreezing. In summer, this SSL is thought of as an ocean water snow layer, with a density of <500 kg m-3. After refreezing in autumn, this layer produces a dense, icy 2-10 cm deep layer at the snow/ice interface and occasionally occupies up to 50% of the snow profile on MYI in winter.. This layer, which has previously not been observed, may, depending on the state of metamorphism and hardness,influence snow water equivalent and snow depth measurements.
This study uses a combination of micro-Computed Tomography measurements to determine geometrical snow properties combined with oxygen isotope analysis to understand the ice origin (atmospheric or marine). We aim to better understand processes at the snow/ice interface on Arctic sea ice and as a result, the infiltration of brine into snow on FYI.
How to cite: Macfarlane, A. R., Dadic, R., Hämmerle, S., Wagner, D. N., and Schneebeli, M.: Quasi in-situ snow and sea ice interface microstructure measured by micro-computed tomography, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-7778, https://doi.org/10.5194/egusphere-egu21-7778, 2021.
The decline of Arctic sea ice extent is one of the most spectacular signatures of global warming, and studies converge to show that this decline has been accelerating over the last four decades, with a rate that was not anticipated by climate models. To improve these models, relying on comprehensive and accurate sea ice thickness and mechanical properties is essential. However, there is a trade-off between accuracy comprehensiveness. On the one hand, estimations from in situ acquisitions such as ice drillings or SONAR surveys are very accurate, but they remain rare and at a local scale. On the other hand, satellite observations allow an average ice thickness estimation at the global scale from the measurement of freeboard, but it remains of poor accuracy. Seismic methods have been known to provide very accurate estimations of both sea ice thickness and mechanical properties since the 1950s, but due to the hostile environment and complicated logistics in the Arctic, such methods have not been given much interest. However, thanks to the rapid technological and methodological progresses of the last 10 years, they have known a regain of interest. In particular, passive seismology has proved very promising for the continuous and autonomous monitoring of sea ice.
This paper introduces a methodological approach for passive monitoring of both sea ice thickness and mechanical properties. To prove this concept, we use data from a seismic experiment where an array of 247 geophones was deployed on sea ice, in a fjord at Svalbard, between 1 and 26 March 2019. From the continuous recording of the ambient seismic field, the empirical Green's function of the seismic waves guided in the ice layer was recovered via the so-called noise correlation function (NCF). By comparing the NCF with recordings from active sources, we demonstrate that it converges towards the Green's function of the ice sheet with a temporal resolution of a few hours. Using specific array processing, the multimodal dispersion curves of the ice layer were calculated from the NCF, and then inverted for the thickness and elastic properties of sea ice via Bayesian inference. The evolution of sea ice properties was monitored for 26 days, and values are consistent with literature, as well as with measurements made directly in the field.
How to cite: Serripierri, A., Moreau, L., Boue, P., and Weiss, J.: Recovering and monitoring the thickness and elastic properties of sea ice from one month of seismic noise in Svalbard, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-10109, https://doi.org/10.5194/egusphere-egu21-10109, 2021.
Melt ponds play a key role for the summery energy budget of the Arctic sea-ice surface. Observational data that enable an integrated understanding and improved formulation of the thermodynamic and hydrological pond system in global climate models are spatially and temporally limited.
Previous studies of shallow water bathymetry of riverbeds and lakes, experimental studies above sea ice and increasing availability of high-resolution aerial sea ice imagery motivated us to investigate the possibilities to derive pond bathymetry from photogrammetric multi-view reconstruction of the summery ice surface topography.
Based on dedicated flight grids and simple assumptions we were able to obtain pond depth with a mean deviation of 3.5 cm compared to manual in situ observations. The method is independent of pond color and sky conditions, which is an advantage over recently developed radiometric retrieval methods.
We present the retrieval algorithm, including requirements to the data recording and survey planning, and a correction method for refraction at the air— pond interface. In addition, we show how the retrieved elevation model synergize with the initial image data to retrieve the water level of each individual pond from the visually determined pond exterior.
The study points out the great potential to derive geometric and radiometric properties of the sea-ice surface emerging from the increasingly available image data recorded from UAVs or aircraft.
How to cite: Fuchs, N., König, M., and Birnbaum, G.: Estimating melt pond bathymetry from aerial images using photogrammetry, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-10214, https://doi.org/10.5194/egusphere-egu21-10214, 2021.
Arctic sea ice has retreated significantly over recent years. This ongoing sea ice decline has major implications for Arctic warming which motivates efforts to improve modeling capabilities. Human activities are also affected as sea ice is becoming less stable making ice roads, on-ice operations, and subsistence activities challenging in certain regions. To enhance modelling capabilities, ice use, and safety near sea ice, it is crucial to understand how sea ice deforms and fractures on the km-scale. Satellite remote sensing provides important insight into the mechanisms of large-scale sea ice deformation. However, analysis is frequently hampered by suboptimal data availability and lacks the spatiotemporal resolution necessary to resolve key processes.
We examine ground-based radar interferometry as a tool to bridge the gap between spaceborne remote sensing and sea ice lab and in-situ measurements during two field campaigns. We deployed a Gamma portable radar interferometer (GPRI) during a drifting ice camp in the Beaufort Sea during spring 2020. Based on this data, we demonstrate the ability to derive km-scale 2-dimensional strain/stress fields through inverse modeling. This analysis also highlights the ability to resolve mm-scale variations in dynamic behavior between different ice regimes. We also deployed a GPRI at a fixed reference point on shore in Utqiaġvik, Alaska. This enabled the tracking of absolute motion over several hours revealing near uni-axial elastic divergence in response to offshore wind.
Our analysis included efforts to remove signals from continuous antenna tilt due to ice motion when stationed on ice. We also needed to take steps to remove atmospheric phase contributions from the data obtained in Utqiaġvik during late spring. Overall, ground-based radar interferometry shows promise as a tool to track mm-scale sea ice dynamics. This may enable new insight into rheological behavior of sea ice and potentially the monitoring of dynamic precursors to fracture, which may improve safety near ice operations.
How to cite: Dammann, D. O., Fedders, E., Mahoney, A., Johnson, M., Meyer, F., and Fahnestock, M.: Ground-based radar interferometry of sea ice dynamics, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-3334, https://doi.org/10.5194/egusphere-egu21-3334, 2021.
In current times of a changing global climate, a special interest is focused on the
large-scale recording of sea ice. Among the existing remote sensing methods, bi-
statically reflected signals of Global Navigation Satellite Systems (GNSS) could
play an important role in fulfilling the task. Within this project, sensitivity of
GNSS signal reflections to sea ice properties like its occurrence, sea ice thick-
ness (SIT) and sea concentration (SIC) is evaluated. When getting older, sea
ice tends go get thicker. Because of decreasing salinity, i.e. less permittivity,
as well as relatively higher surface roughness of older ice, it can be assumed
that reflected signal strength decreases with increasing SIT. The reflection data
used were recorded in the years 2015 and 2016 by the TechDemoSat-1 (TDS-1)
satellite over the Arctic and Antarctic. It includes a down-looking antenna for
the reflected as well as an up-looking antenna dedicated to receive the direct sig-
nal. The raw data, provided by the manufacturer SSTL, were pre-processed by
IEEC/ICE-CSIC to derive georeferenced signal power values. The reflectivity
was estimated by comparing the power of the up- and down-looking links. The
project focuses on the signal link budget to apply necessary corrections. For this
reason, the receiver antenna gain as well as the Free-Space Path Loss (FSPL)
were calculated and applied for reflectivity correction. Differences of nadir and
zenith antenna FSPL and gain show influence of up to 6 dB and −9 dB to 9 dB
respectively on the recorded signal strength. All retrieved reflectivity values are
compared to model predictions based on Fresnel coefficients but also to avail-
able ancillary truth data of other remote sensing missions to identify possible
patterns: SIT relations are investigated using Level-2 data of the Soil Moisture
and Ocean Salinity (SMOS) satellite. The SIC comparison was done with an
AMSR-2 product. The results show sensitivity of the reflectivity value to both
SIT and SIC simultaneously, whereby the surface roughness is also likely to
have an influence. This on-going study aims at the consolidation of retrieval
algorithms for sea-ice observation. The resolution of different ice types and the
retrieval of SIT and SIC based on satellite data is a challenge for future work
in this respect.
How to cite: Kreß, F., Semmling, M., Cardellach, E., Li, W., Hoque, M., and Wickert, J.: Surface reflectivity in polar regions retrieved from TDS-1 mission data, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-13036, https://doi.org/10.5194/egusphere-egu21-13036, 2021.
The seasonal snowpack is a globally important water resource that is notoriously difficult to measure. Existing instruments make measurements of falling or accumulating snow water equivalent (SWE) that are susceptible to bias, and most can represent only a point in the landscape. Furthermore the global array of SWE sensors is too sparse and too poorly distributed to be an adequate constraint on snow in weather and climate models. We present a new approach to monitoring snowpack SWE from time series of lake water pressure. We tested our method in the lowland Finnish Arctic and in an alpine valley and high-mountain cirque in Switzerland, and found that we could measure changes in SWE and their uncertainty through snowfalls with little bias and with an uncertainty comparable to or better than that achievable by other instruments. More importantly, our method inherently senses change over the whole lake surface which can be several square kilometres, or hundreds of million of times larger than the aperture of a pluviometer. This large scale makes our measurements directly comparable to the grid cells of weather and climate models. We find, for example, snowfall biases of up to 100% in operational forecast models AROME-Arctic and COSMO-1. Seasonally-frozen lakes are widely distributed at high latitudes and are particularly common in mountain ranges, hence our new method is particularly well suited to the widespread, autonomous monitoring of snow-water resources in remote areas that are largely unmonitored today. This is potentially transformative in reducing uncertainty in regional precipitation and runoff in seasonally-cold climates.
How to cite: Pritchard, H., Farinotti, D., and Colwell, S.: Measuring changes in snowpack SWE continuously on a landscape scale using lake water pressure, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-7507, https://doi.org/10.5194/egusphere-egu21-7507, 2021.
In cold regions, the seasonal snowpack plays an important hydrological role. By storing and releasing solid precipitation, the snowpack gives shape to the yearly hygrogram. In addition, by modulating liquid water pathway and residence time, snowpack internal conditions have a strong implication on the partitioning of meltwater among streamflow, groundwater recharge and soil moisture storage. During rain on snow (ROS) events, snowpack conditions influence timing and amount of liquid water inflow to the surface drainage system, with winter floods and ice jams as potential consequences.
Recent observations and projections show an increase in ROS frequency in many cold regions of the world. This trend raises concern about a possible increase in winter floods and ice jams events with climate change. In order to better anticipate the hydrological consequences of the increasing ROS phenomenon, a good understanding of the processes and conditions influencing liquid water release from the snowpack is required.
The present study articulates around a multimethod approach to characterize liquid water storage and movement in a snowpack in a non-mountainous environment. By combining drone-based high frequency GPR, NIR photogrammetry, time domain reflectometry, stable isotopes of water and other manual measurements throughout a winter season, we aim monitoring the spatiotemporal evolution of the snowpack liquid water content as well as the water fluxes at the snowpack margins.
Preliminary results show that, combining the selected methods allows tracking liquid water storage and movements in the snowpack throughout an entire season.
How to cite: Valence, E. and Baraër, M.: Impact of the spaciotemporal variability of the snowpack conditions on internal liquid water fluxes, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-6467, https://doi.org/10.5194/egusphere-egu21-6467, 2021.
Terrestrial snow cover is a perennial feature throughout the global cryosphere, taking the form of individual snow patches during summer and becoming more spatially continuous in winter. The characteristics and conditions of these snowpacks can be altered by rapid changes in temperature and precipitation, significantly impacting local ecosystems, upland hydrology and snow avalanche risks. In Scotland, for example, monitoring the hazards associated with snowpack alterations is a central focus of the Scottish Avalanche Information Service (SAIS) and is essential to ensuring the safety of local communities, hill walkers and mountaineers. In this context, the development of new remote sensing techniques for snow monitoring will help the SAIS develop avalanche forecasts and potentially without the need to undertake arduous and dangerous fieldwork. Here, we aim to develop the utility of millimetre-wave radar at 94 GHz as a new remote sensing tool for monitoring snowpacks. We use a ground-based 94 GHz, real-aperture system called AVTIS2 which mechanically scans across a scene of interest to generate radar backscatter images and 3D Digital Elevation Models (DEMs). AVTIS2 uses a narrow beamwidth of 0.35° (i.e. a spot size of 6 m per km) and has a maximum range of ~6 km, enabling kilometre-scale mapping at high angular resolution. This radar system has previously been successful in monitoring the topographic changes of volcanic lava domes, measuring the dynamics of active lava flows and quantifying 94 GHz radar backscatter from glacier ice. We aim to deploy the AVTIS2 millimetre-wave radar in the Cairngorms National Park, Scotland, in January/February 2021 and validate our measurements with a co-located Terrestrial Laser Scanner (TLS). Additionally, we will acquire in situ observations of snow properties to gain a better understanding of how 94 GHz radar signals interact with the snowpack. Overall, we will report on the following: (1) the radar backscatter characteristics from a variety of snow surface conditions at millimetre wavelengths; (2) point cloud and DEM differences between AVTIS2 and TLS measurements over snow-covered terrain; and (3) the effect of snowpack properties on radar backscatter and how this can be used to understand snow-associated hazards.
How to cite: Harcourt, W. D., Robertson, D., Macfarlane, D., Rea, B., James, M., Fyffe, B., and Diggins, M.: 94 GHz radar mapping of terrestrial snow cover, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-2747, https://doi.org/10.5194/egusphere-egu21-2747, 2021.
Comprehensive descriptions of the seismic properties of glaciers and ice masses require that both compressional (P-) and shear (S-) wave components are considered. Among these properties is the seismic attenuation, expressed by the Quality Factor (Q). Q is valuable for two reasons: first, to correct measurements of seismic amplitude for wavelet propagation effects, as in reflection amplitude-versus-angle (AVA) studies. Second, Q is an indicator of ice properties such as temperature and impurity content, and laboratory/field studies of soils and geological materials suggests that the ratio of the compressional- and shear-wave quality factors, Qp/Qs, may indicate fluid saturation (particularly when considered jointly with the velocity ratio Vp/Vs). Thus, a measurement of Qp/Qs could usefully inform the hydrological structure of the firn and indicate variations in the density of the firn column.
Despite its importance, few studies appear to have measured Qp in firn columns and none appear to have measured Qs in firn. Doing so for either compressional- or shear-wave arrivals is challenging, due to the ray paths followed by the diving wave first arrivals and their accurate representation in attenuation measurement methods. In preparation for an AVA study of bed properties at Korff Ice Rise, West Antarctica, we have used spectra of diving wave first arrivals and a modified spectral-ratio method to measure Qp and Qs as a function of depth in the firn column. Shot gathers with vertically oriented geophones at offsets of 2.5 - 1000m were used to measure Qp. For detecting the shear component, the geophones were oriented horizontally; in this configuration, diving and reflected shear phases were recorded with high signal-to-noise ratios. The variation of Q with depth is represented as discrete constant-Q layers with thicknesses between 6 and 27 m. Qp shows progressive increases in depth from 21 ± 3 in the uppermost 20 m (where Vp < 3000 m/s), to 246 ± 30 between 74 and 80 m depth (3750 m/s < Vp < 3770 m/s). Qs increases from 14 ± 4 in the uppermost 20m, to 80 ± 6 between 80 and 90m depth. The ratio Qp/Qs varies throughout the depths measured, from Qp/Qs ~ 1.5 at the surface, to Qp/Qs ~ 3 at 80 m. This is broadly consistent with previously quoted values, but the variation may imply that Qp/Qs is influenced by firn structure.
Similar measurements at a variety of sites could help to inform a relationship between Qp, Qs and firn properties. In the immediate future, the measurement of Q in the firn will aid measurements of bed reflectivity, and help to determine the material properties of the ice-bed interface.
How to cite: Agnew, R., Clark, R., Booth, A., and Brisbourne, A.: Seismic quality factor measured for compressional and shear waves in the firn column of Korff Ice Rise, West Antarctica, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-7556, https://doi.org/10.5194/egusphere-egu21-7556, 2021.
Full Waveform Inversion (FWI) is a well-established seismic imaging technique used in the exploration industry to acquire high resolution, high precision velocity models of the subsurface from seismic data. Although FWI is computationally expensive and requires customized data acquisition, the technique has the potential to improve subsurface glaciological imaging.
Firn is formed as an intermediate material (of density ~400 – 810 kg m-3) as snow is compressed into ice (~810 – 917 kg m-3). Variations in surface conditions and periods of surface melting commonly lead to the presence of discrete layers and lenses of refrozen (‘infiltration’) ice within the firn column; layers that can be from millimetres to several tens of metres thick. Therefore, firn characteristics provide a tool for reconstructing climate conditions relating to the amount of snow accumulation, melt, temperature conditions and subsequent snow preservation. Given the complexity of these relationships, it has not been possible to develop a theoretical model that predicts accurately variations in firn properties or density with depth. Consequently, seismic techniques, which are logistically less demanding than extracting firn cores, are typically used to reconstruct these physical properties of the firn column.
Firn seismic velocity is often derived from seismic data using the Herglotz-Wiechert (HW) inversion. A velocity trend would be expected to increase from ~400 m s-1 in snow through to ~3,800 m s-1 in ice. Thus, the presence of infiltration ice within the firn column results in anomalously high velocity intervals at shallow depths. HW inversion can be limited by the accuracy of first-break picking (specifically in the near offset, where a small error in the travel time pick gives the greatest variability to the HW velocity output), and it cannot recover the velocity inversion below a refrozen ice layer without elastodynamic redatumming. Importantly, FWI has the capacity to mitigate issues such as these, and thereby potentially offers a new standard for glaciological seismic modelling.
Using seismic datasets obtained from Pine Island Glacier, Antarctica, and synthetic data that simulate firn columns that include substantial thicknesses of infiltration ice (‘ice slabs’, up to 100 m thick and from 5-80 m deep), we show how FWI improves on current seismic techniques in terms of identifying the velocity variations associated with both included ice layers and the firn underlying them. We present a best practice methodology for the use of FWI with glaciological data, including (i) the extraction of a source wavelet from the data for the use with modelling, (ii) the steps needed to ensure a consistent waveform, (iii) the appropriate offset-to-depth ratio, and (iv) the requirement of a constraint for the uppermost part of the velocity model. Finally, we evaluate the robustness of the FWI approach by comparing it with well-established HW methods for building velocity models.
How to cite: Pearce, E., Booth, A., Rost, S., Sava, P., Brisbourne, A., Jones, I., and Hubbard, B.: Full Waveform Inversion (FWI) for glaciological seismic data –Improving the seismic characterisation of glacier firn, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-916, https://doi.org/10.5194/egusphere-egu21-916, 2021.
Antarctic ice sheet history is imprinted in the structure and fabric of the ice column. At ice rises, the signature of ice flow history is preserved due to the low strain rates inherent at these independent ice flow centres. We present results from a distributed acoustic sensing (DAS) experiment at Skytrain Ice Rise in the Weddell Sea Sector of West Antarctica, aimed at delineating the englacial fabric to improve our understanding of ice sheet history in the region. This pilot experiment demonstrates the feasibility of an innovative technique to delineate ice rise structure. Both direct and reflected P- and S-wave energy, as well as surface wave energy, are observed using a range of source offsets, i.e., a walkaway vertical seismic profile (VSP), recorded using fibre optic cable. Significant noise, which results from the cable hanging untethered in the borehole, is modelled and suppressed at the processing stage. At greater depth, where the cable is suspended in drilling fluid, seismic interval velocities and attenuation are measured. Vertical P-wave velocities are high (VINT = 4029 ± 244 m s-1) and consistent with a strong vertical cluster fabric. Seismic attenuation is high (QINT = 75 ± 12) and contrary to observations in ice sheets over this temperature range. The signal level is too low, and the noise level too high, to undertake analysis of englacial fabric variability. However, modelling of P- and S-wave traveltimes and amplitudes with a range of fabric geometries, combined with these measurements, demonstrates the capacity of the DAS method to discriminate englacial fabric distribution. From this pilot study we make a number of recommendations for future experiments aimed at quantifying englacial fabric to improve our understanding of recent ice sheet history.
How to cite: Brisbourne, A., Kendall, M., Kufner, S., Hudson, T., and Smith, A.: Downhole distributed acoustic seismic profiling at Skytrain Ice Rise, West Antarctica, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-11803, https://doi.org/10.5194/egusphere-egu21-11803, 2021.
Seismic surveys are widely used to study the properties of glaciers, basal material and conditions, ice temperature and crystal orientation fabric. The emerging technology of Distributed Acoustic Sensing (DAS) uses fibre optic cables as pseudo-seismic receivers,
reconstructing seismic measurements at a higher spatial and temporal resolution than is possible using traditional geophone deployments. DAS generates large volumes of data, especially in passive mode, which can be costly in time and cumbersome to analyse. Machine learning tools provide an effective means of automatically identifying events within these records, avoiding a bottleneck in the data analysis process. Here we present initial trials of machine learning for a borehole-deployed DAS system on Store Glacier, West Greenland. Data were acquired in July 2019, using a Silixa iDAS interrogator and a BRUsens fibre optic cable installed in a 1043 m-deep borehole. The interrogator sampled at 4000 Hz, recording both controlled-source Vertical Seismic Profiles (VSPs), made with hammer-and-plate source, and a 3-day passive record of cryoseismicity.
We used a Convolutional Neural Network (CNN) to identify seismic events within the seismic record. A CNN is a deep learning algorithm that uses a series of convolutional filters to extract features from a 2-dimensional matrix of values. These features are then used to train a model
that can recognise objects or patterns within the dataset. CNNs are a powerful classification tool, widely applied to the analysis of both images and time series data. Previous research has demonstrated the ability of CNNs to recognise seismic phases in time series data for long-range
earthquake detection, even when the phases are masked by a low signal-to-noise ratio. For the Store Glacier data, initial results were obtained using a CNN trained on hand-labelled, uniformly-sized windows. At present, these windows have been targeted around high signal-to-noise ratio seismic events in the controlled-source VSPs only. Once trained, the CNN achieved accuracy of 90% in recognising whether new windows contained coherent seismic
The next phase of analysis will be to assess the performance of the CNN when trained and tested on large passive DAS datasets. The method will then be used for the identification and flagging of seismic events within the passive record for interpretation and event location. The identified signals will be used to provide information on the glacier’s seismic velocity structure, ice temperature and ice crystal orientation fabric and anisotropy. Basal reflections were identified and will be used to provide information on subglacial material properties and conditions of Store Glacier. The efficiency of the CNN allows detailed insight to be made into the origins and style of glacier seismicity, facilitating further advantages of passive DAS instrumentation.
How to cite: Pretorius, A., Smith, E., Booth, A., Christofferson, P., Nowacki, A., de Ridder, S., Schoonman, C., Clarke, A., Hubbard, B., Chudley, T., Law, R., Doyle, S., and Chalari, A.: Application of machine learning methods to identify englacial seismicity in a Distributed Acoustic Sensing dataset from Store Glacier, West Greenland, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-7448, https://doi.org/10.5194/egusphere-egu21-7448, 2021.
Ice shelves are widely known to slow the transfer of Antarctic grounded ice to the ocean, especially if their flow is decelerated by local pinning points. Their longevity is influenced by variations in ice dynamics, surface accumulation and oceanic conditions in the ice shelf cavity. This is reflected in the ice shelf structure, which can be characterized by the shape of internal radar reflection horizons.
We aim to map the internal ice shelf stratigraphy of ice shelves, starting with the narrow belt of ice-shelves in the Dronning Maud Land area. The final goal will be to evaluate these as a spatiotemporal archive of ice provenance and ice dynamics. The bulk of the data presented here were collected with AWI’s airborne multi frequency ultra-wideband radar and we combine these new observations with airborne and ground-based radar surveys from previous years. We present a consistent set of internal radar isochrones on a catchment scale for the Roi Baudoin area including the Ragnhild ice streams, the grounding-zone, the iceshelf and multiple ice rises. Using pattern matching technique we can link isochrones across different ice rises in the area, and hence provide first observational constraints on how ice rises jointly react to changes in atmospheric and oceanographic forcings. We also find a number of interesting features including dynamically induced dips in shear zones, truncating layers at the ice-shelf base, and the development of a meteoric ice layer distinguishing advected from newly accumulated ice in the iceshelf. The time series provided by radar observations over the last 10 years also offers the potential to map temporal changes. We use ice-flow modelling to provide age constraints for some internal layers and delineate portions within the shelf as a function of their advection history, hence marking areas of differing rheologies within the shelf. Taken together, this case study on a catchment scale is a primer to unravel the information stored in the isochronal stratigraphy of coastal Antarctica and contributes to international efforts (e.g., SCAR AntArchitecture) of mapping stratigraphy on ice sheet scales.
How to cite: Koch, I., Drews, R., Jansen, D., Franke, S., Visnjevic, V., Eisen, O., Oraschewski, F., and Pattyn, F.: Ice shelf internal reflection horizons reveal ice provenance, dynamics, surface accumulation and oceanic melt, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-15794, https://doi.org/10.5194/egusphere-egu21-15794, 2021.
The North East Greenland Ice Stream clearly stands out in the surface velocity field of the ice flow of Greenland, with its sharp and narrow shear margins visible in the flow field almost up to the central divide. While the current extent and strength of the streaming can be determined from remotely sensed velocities of the ice surface, it is less known how the ice stream is affecting the deeper layers of ice in its catchment area, and how it may have evolved over time. The deformation of the ice due to streaming can be made visible by mapping the distortion of the isochronous stratigraphy of the ice. This has been done by an airborne radar survey centering on the location of the EGRIP drilling camp, carried out with the ultra wide band radar system (AWI UWB). The dense grid of profiles arranged mainly perpendicular to the ice flow reveals the imprint that the strong shearing leaves within the layering of the ice. Although the layers are tightly folded and distorted within the shear zones, it is possible to continuously trace reflections within the upper half of the ice column throughout the entire survey area. It can be shown that the intensity of the folding is linked to the strain rate field derived from the surface velocities, and that the deformation history of the ice is preserved in the folded layers, even after it is no longer affected by high strain rates. The advection patterns of the mapped stratigraphic features reveal how the streaming of the ice and the resulting local changes of surface topography may have affected the inflow into the stream and the position of the shear margins over time.
How to cite: Jansen, D., Franke, S., Binder, T., Bons, P., Dahl-Jensen, D., Eisen, O., Miller, H., Paden, J., and Weikusat, I.: Interior of an ice stream: 3-D geometry of distorted radar stratigraphy of upstream NEGIS and vicinity., EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-15382, https://doi.org/10.5194/egusphere-egu21-15382, 2021.
Crystal anisotropy of ice causes slight birefringence for electromagnetic waves. At the same time, the mechanical anisotropy amounts to several orders of magnitude, thus making fabric properties highly-relevant for internal deformation. To date, bulk anisotropy of glaciers and ice sheets can be determined by geophysical methods, such as polarimetric radar, or direct sampling from ice cores. A shortcoming has been so far that changes of bulk anisotropy could mainly be inferred at single point observations, but less so as continuous profiles. Here, we exploit the effect of birefringence caused by bulk anisotropy in co-polarized airborne radar data to determine the horizontal anisotropy across the North-East Greenland Ice Stream. We base our analysis on the fact that birefringence causes a second-order effect on radar amplitudes, which leads to a beat frequency in the low and medium frequency range (O(100 kHz)), which is proportional to the horizontal anisotropy. Complementing our radar analysis with direct fabric and dielectric property observations we can constrain the range of all three fabric eigenvalues as a function of space across and along the ice stream. Finally, we assess the effect of the inferred fabric distribution on the overall ice rheology in the context of ice stream dynamics. Our overall approach has the advantage that it can be applied to co-polarized radar systems, as commonly used in profiling surveys, and does not require dedicated cross-polarized radar set-up. This provides the opportunity to revisit older data, especially from Greenland and Antarctica, to map fabric anisotropy in ice-dynamically interesting regions.
How to cite: Eisen, O., Franke, S., Jansen, D., Paden, J., Drews, R., Ershadi, M. R., Steinhage, D., Lilien, D., Yan, J., Weikusat, I., Wilhelms, F., Dahl-Jensen, D., Grindsted, A., Hvidberg, C., and Miller, H.: Fabric beats in radar data across the NEGIS ice stream, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-1207, https://doi.org/10.5194/egusphere-egu21-1207, 2021.
Investigating the physical conditions underlying and enabling fast glacier flow is crucial to understanding the future stability of ice sheets, as well as their impact on future sea-level rise. Seismic surveys have been widely used to measure material properties of the ice and substrate, including seismic velocity structure, anisotropy, and bed properties. While traditional seismic surveys rely on natural seismicity or man-made sources such as explosives, anthropogenic noise generated through ice-core drilling can also be used as a seismic source. Placing geophones around an ice-core drilling site therefore presents an exciting opportunity to complement and extend measurements from ice cores to the surrounding area.
Here, we present preliminary results from a seismic investigation conducted using noise generated by ice-core drilling activities at the East Greenland Ice Core Project (EGRIP) site. The EGRIP site is located near the onset region of the Northeast Greenland Ice Stream (NEGIS), which drains over 10% of the Greenland Ice Sheet. The ice-core drilling process creates a variety of semi-continuous (e.g., generator-induced) and impulsive (e.g., core break) seismic source signals. As drilling progresses through the ice column, the corresponding variation in seismic signals can be used to generate a vertical profile of seismic properties. In the summer of 2019, nine 3-component surface geophones were deployed at 0, 300, 750, 1500 and 3000 m distance from the drill site along two lines corresponding to the along- and cross-flow directions of the ice stream. The network recorded at a sampling frequency of 400 Hz for 28 days, during which drilling progressed between 1920 and 2110 m depth below the surface. Both continuous and impulsive sources related to the drilling process were recorded at all stations. Impulsive arrivals were identified using STA/LTA phase-picking across multiple components and stations. Because the depth of the drill head at any given time is known, the move-out of each event could then be used to determine the integrated seismic velocity structure along the source-receiver ray path.
Additionally, sporadic passive microseismic signals resulting from ice stream motion over the bed were observed at all stations. Both individually distinguishable icequakes and 3-5 minute-long “gliding” tremors were recorded, indicative of stick-slip motion at the bed of NEGIS. Further work will concentrate on modelling these tremors to resolve the shear modulus of the substrate, and on incorporating continuous drill-generated noise into our overall analysis. Our approach demonstrates the added value of opportunistic seismic networks as a complement to ice drilling operations.
How to cite: Schoonman, C., Eisen, O., Hofstede, C., Stoll, N., Franke, S., and Smith, E. C.: Investigating seismic properties of the NEGIS onset region using ice-drilling noise as a seismic source, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-9964, https://doi.org/10.5194/egusphere-egu21-9964, 2021.
The ice crystal structure and in particular the crystal orientation fabrics (COF) provide valuable information about the deformation history of ice sheets and glaciers. Therefore, COF analysis has been among the standard measurement techniques for most deep ice core drilling projects in the last three decades. The analysis depends on carefully prepared thin sections of ice that are measured with cross-polarised light microscopy or electron backscattering and diffraction (EBSD). The preparation of thin sections is labour-intensive and therefore only a discrete number of samples along the ice core is usually analysed. Geophysical methods such as ultrasonic sounding along the ice core could be employed to complement the discrete fabric data by providing data to fill the gaps. A suitable method needs to be reasonably fast, ideally non-invasive and provides unambiguous information in combination with the established methods.
In our study, we demonstrate the feasibility of such ultrasonic experiments applied to an ice core to support the approved cross-polarised light microscopy method. Point-contact transducers transmitted ultrasonic waves into ice core samples from a temperate glacier. X-ray computer tomography measurements provide the required information to consider the effect of a two-phase medium (ice and air bubbles) in a porosity correction of the velocity. We determined the azimuthal variation of the seismic velocity. This variation is a result of seismic anisotropy due to the crystal orientation within the ice core volume. The measurements can be acquired within minutes and do not require an extensive preparation of ice samples.
In addition, the COF of adjacent ice core samples was measured with cross-polarised light spectroscopy. From this, we derived the elasticity tensor and finally calculated the associated seismic velocities for the same azimuth and inclination angle as for the ultrasonic experiments. We compare these two velocity profiles and discover a significant discrepancy in presence of large ice grains. However, with an increasing number of ice grains both methods provide similar results. Although the ultrasonic measurements reveal some ambiguities, these can be resolved when considering the information derived from the standard analysis.
We conclude that ultrasonic measurements along the ice core are suitable to support the established COF analysis for sufficiently small grains as found in polar cores. We recommend further exploration of the potential of the presented technique as it provides both the chance to obtain a continuous fabric profile and a direct link to large-scale seismic measurements in the vicinity of ice core drilling sites.
How to cite: Hellmann, S., Kerch, J., Grab, M., Löwe, H., Bauder, A., Weikusat, I., and Maurer, H.: Ultrasonic velocity experiments on ice cores to complement fabric measurements, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-6100, https://doi.org/10.5194/egusphere-egu21-6100, 2021.
Glacier dynamics exhibits a strong variability in response to climate forcing. To better understand the effects of this forcing, it is essential to provide continuous deformation measurements that must be long-term (over a full or several melt seasons) and high-resolution (from daily to sub-daily). GNSS monitoring represents a valuable mean to better apprehend mechanisms of basal sliding and provide high-resolution 3D constraints on physical models of glacier flow. In this study, we investigate motions and deformations of the Argentière Glacier in the French Alps at 2400 m altitude, derived from up to 12 permanent GNSS stations continuously operating since April 2019, covering two melting seasons. The Argentière glacier is particularly interesting due to (i) its long-term subglacial observatory measuring basal sliding velocity and subglacial discharge, and (ii) the wide range of complementary observations currently being acquired there, which give access to internal ice deformation thanks to tiltmeters in boreholes, and to basal stick-slip and englacial fracturing thanks to seismic observations. We present the results (i) over relatively long timescales (days to months) using the fast static positioning approach to evaluate mean variations and compare to the independent measurements mentioned above, and (ii) kinematic approach to focus on high temporal resolution velocity variations during specific short-term events that cannot be seen from the static processing. The horizontal surface velocities on daily time scales reveal spring acceleration due to meltwater followed by steadily high velocities over the summer, and significant episodic accelerations in the fall in response to the storm events. We quantify strain rates and their evolution in time that can be related to the vertical surface motions. We combine the GNSS with the englacial tiltmeters results to deduce the basal speed variations. The GNSS confrontation with other independent observations also allows analyzing the surface motions that combine horizontal speed-ups with uplift due to bed separation of the ice sheet. We will further search for evidence for surface motions that might occur in daily cycles in summer, as hinted at by the basal sliding measurements. But before analyzing daily cycles of glacier motions, it is critical to remove positioning artefacts due to multipath effects with a repeat period close to 24 hours. These effects are enhanced on the Argentière Glacier by the limited number of visible satellites in the narrow valley. Moreover, it evolves with the dynamically changing environment (snow accumulation and snowmelt that create variations in ground reflectivity properties). A multi-GNSS analysis combining GPS and GLONASS data helps overcome the lack of satellite data and increase the time resolution on a sub-daily scale. If daily cycles are resolvable from the improved GNSS analysis, their phase offsets with respect to meteorological, hydrological and seismic observations can give us indices of eventual mechanisms of sliding at the bedrock interface.
How to cite: Togaibekov, A., Walpersdorf, A., Gimbert, F., Vincent, C., Helmstetter, A., Six, D., Moreau, L., Roldan-Blasco, J. P., Ott, L., Mercier, S., Laarman, O., Piard, L., Nanni, U., Matthey, M., Urruty, B., Sue, C., Bouvier, J.-N., Radiguet, M., Romeyer, O., and Mugnier, J.-L.: Three-dimensional surface velocity variations of the Argentière glacier (French Alps) monitored with a high-resolution continuous GNSS network, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-13230, https://doi.org/10.5194/egusphere-egu21-13230, 2021.
The warming of alpine bedrock permafrost in the last three decades and consequent reduction of frozen areas has been well documented. Its consequences like slope stability reduction put humans and infrastructures at high risk. 2020 in particular was the warmest year on record at 3000m a.s.l. embedded in the warmest decade.
Recently, the development of electrical resistivity tomography (ERT) as standard technique for quantitative permafrost investigation allows extended monitoring of this hazard even allowing including quantitative 4D monitoring strategies (Scandroglio et al., in review). Nevertheless thermo-hydro-mechanical dynamics of steep bedrock slopes cannot be totally explained by a single measurement technique and therefore multi-approach setups are necessary in the field to record external forcing and improve the deciphering of internal responses.
The Zugspitze Kammstollen is a 850m long tunnel located between 2660 and 2780m a.s.l., a few decameters under the mountain ridge. First ERT monitoring was conducted in 2007 (Krautblatter et al., 2010) and has been followed by more than one decade of intensive field work. This has led to the collection of a unique multi-approach data set of still unpublished data. Continuous logging of environmental parameters such as rock/air temperatures and water infiltration through joints as well as a dedicated thermal model (Schröder and Krautblatter, in review) provide important additional knowledge on bedrock internal dynamics. Summer ERT and seismic refraction tomography surveys with manual and automated joints’ displacement measurements on the ridge offer information on external controls, complemented by three weather stations and a 44m long borehole within 1km from the tunnel.
Year-round access to the area enables uninterrupted monitoring and maintenance of instruments for reliable data collection. “Precisely controlled natural conditions”, restricted access for researchers only and logistical support by Environmental Research Station Schneefernerhaus, make this tunnel particularly attractive for developing benchmark experiments. Some examples are the design of induced polarization monitoring, the analysis of tunnel spring water for isotopes investigation, and the multi-annual mass monitoring by means of relative gravimetry.
Here, we present the recently modernized layout of the outdoor laboratory with the latest monitoring results, opening a discussion on further possible approaches of this extensive multi-approach data set, aiming at understanding not only permafrost thermal evolution but also the connected thermo-hydro-mechanical processes.
Krautblatter, M. et al. (2010) ‘Temperature-calibrated imaging of seasonal changes in permafrost rock walls by quantitative electrical resistivity tomography (Zugspitze, German/Austrian Alps)’, Journal of Geophysical Research: Earth Surface, 115(2), pp. 1–15. doi: 10.1029/2008JF001209.
Scandroglio, R. et al. (in review) ‘4D-Quantification of alpine permafrost degradation in steep rock walls using a laboratory-calibrated ERT approach (in review)’, Near Surface Geophysics.
Schröder, T. and Krautblatter, M. (in review) ‘A high-resolution multi-phase thermo-geophysical model to verify long-term electrical resistivity tomography monitoring in alpine permafrost rock walls (Zugspitze, German/Austrian Alps) (submitted)’, Earth Surface Processes and Landforms.
How to cite: Scandroglio, R., Rehm, T., Limbrock, J. K., Kemna, A., Heinze, M., Pail, R., and Krautblatter, M.: Decennial multi-approach monitoring of thermo-hydro-mechanical processes, Kammstollen outdoor laboratory, Zugspitze (Germany), EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-13815, https://doi.org/10.5194/egusphere-egu21-13815, 2021.
Two high arctic expeditions have been organized to use seismic methods to recognize the shape of the permafrost along inclined profile between the coast and the mountain slope in two seasons: with the unfrozen ground (October 2017) and frozen ground (April 2018). For measurements, a stand-alone seismic stations has been used with accelerated weight drop with in-house modifications and timing system. Seismic profiles were acquired in a time-lapse manner and were supported with continuous temperature monitoring in shallow boreholes.
Joint interpretation of seismic data using Multichannel analysis of surface waves, First arrival travel-time tomography and Reflection imaging show clear seasonal changes affecting the permafrost where apparent P-wave velocities are changing from 3500 to 5200 m/s. This confirms the laboratory measurements showing doubling the seismic velocity of water-filled high-porosity rocks when frozen. Independent refraction seismic analysis in two seasons shows in average 10 m thick sedimentary layer on top of compacted bedrock. In sediments P wave velocity is changing from 1500 m/s to 4000 m/s between seasons. Velocities in the bedrock are also changing from 4000 m/s to 5500 m/s. Moreover, tomographic interpretation shows that significant change in P wave velocities is observed down to 30 meters.
Such unusual active layer behavior is confirmed in in-situ thermal observations with above 0C temperatures at the depth of 19m. Those observations can be explained with strong underground flow during the frozen period confirmed with borehole.
This research was funded by the National Science Centre, Poland (NCN) Grant UMO-2015/21/B/ST10/02509.
How to cite: Majdanski, M., Marciniak, A., Owoc, B., Dobiński, W., Wawrzyniak, T., Osuch, M., Nawrot, A., and Glazer, M.: Surprisingly thick active layer of permafrost in the mountain slope in the SW Svalbard, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-2206, https://doi.org/10.5194/egusphere-egu21-2206, 2021.
A class of short-duration seismic events were recorded on dense, temporary geophone arrays deployed in Adventdalen, Svalbard in spring and autumn 2019. A similar class of events have also been detected in seismic records from the SPITS seismic array located on Janssonhaugen in Adventdalen, that has been in continuous operation since the 1990’s. In both cases, estimated source positions are dominantly local and cluster around frost polygon, ice-wedge geomorphologies. Correlation with periods of rapidly cooling air temperature and consequent thermal stress build-up in the near surface are also observed. These events are consequently interpreted as frost quakes, a class of cryoseism. The dense, temporary arrays allowed high quality surface-wave dispersion images to be generated, that show potential to monitor structure and change in permafrost through passive seismic deployments. While the lower wavenumber resolution of the sparser SPITS array is less suited to imaging the near-surface in detail, the long continuous recording period gives us a unique insight into the temporal occurrence of frost quakes. This allows us, for example, to better understand the dynamic processes leasing to frost quakes by correlating temporal occurrence with models of thermal stress in the ground, constrained by thermistor temperature measurements from a nearby borehole.
How to cite: Romeyn, R., Hanssen, A., Köhler, A., Ruud, B. O., Stemland, H. M., and Johansen, T. A.: Frost quakes – the sound of a dynamic cryosphere and a convenient source for passive surface wave imaging of permafrost, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-8617, https://doi.org/10.5194/egusphere-egu21-8617, 2021.
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