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CR2.1

Geophysical and in situ methods for snow and ice studies

Geophysical and in-situ measurements offer important baseline datasets, as well as validation for modelling and remote sensing products. They are used to advance our understanding of firn, ice-sheet and glacier dynamics, sea ice processes, changes in snow cover and snow properties, snow/ice-atmosphere-ocean interactions, permafrost degradation, geomorphic mechanisms and changes in englacial and subglacial condition.

In this session we welcome contributions related to a wide spectrum of methods, including, but not limited to, advances in radioglaciology, active and passive seismology, geoelectrics, acoustic sounding, fiber-optic sensing, GNSS reflectometry, signal attenuation and time delay techniques, cosmic ray neutron sensing, ROV and drone applications, and electromagnetic methods. 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. We have been running this session for nearly a decade and it always produces lively and informative discussion. This session is offered as a fully hybrid vPICO: an engaging presentation format in which all authors will present their research orally as a quick-fire 2-minute overview, and then further present and discuss their research.

Co-organized by GI5/HS13/SM5
Convener: Franziska KochECSECS | Co-conveners: Emma C. SmithECSECS, Polona Itkin, Winnie ChuECSECS
Presentations
| Wed, 25 May, 08:30–11:50 (CEST), 13:20–14:50 (CEST)
 
Room N2

Wed, 25 May, 08:30–10:00

Chairpersons: Franziska Koch, Polona Itkin

08:30–08:32
Session Introduction

08:32–08:42
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EGU22-1002
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ECS
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solicited
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On-site presentation
Rebecca Gugerli et al.

Temporally continuous measurements of the snow water equivalent (SWE) are a key variable in many hydrological, meteorological and glaciological studies and are of particular importance in high mountain regions. Obtaining temporally continuous, accurate and reliable SWE observations in these harsh environments, however, remains a challenge. Recently, promising results have been achieved by using a neutronic cosmic ray snow gauge (n-CRSG). The n-CRSG device is deployed below the seasonal snowpack and counts fast neutrons from the secondary cascades of cosmic rays, which are efficiently moderated and absorbed by the hydrogen atoms contained in the snowpack. Based on the exponential relationship between neutrons and hydrogen atoms, we can infer SWE from the neutron count rate. We have installed and evaluated a n-CRSG on the Swiss Glacier de la Plaine Morte. Our validation with 22 manual measurements over five winter seasons (2016/17-2020/21) showed an average underestimation of -2% ±10% (one standard deviation).
In the present study, we explore the use of muons instead of neutrons to infer SWE. To this end, we deployed two muonic cosmic ray snow gauges (µ-CRSG), one below and one above the seasonal snowpack, for the winter season 2020/21 on the same glacier site in Switzerland. The difference in count rates between the top and bottom device can be related to the SWE of the snowpack. We derive a first-cut conversion function based on manual SWE observations by means of snow pits and snow cores. To evaluate the measurements by the µ-CRSG, we also compare them to SWE estimates by the n-CRSG. Over the winter season 2020/21, almost up to 2000 mm w.e. were observed. Overall, the µ-CRSG agrees well with the n-CRSG on the evolution of the snowpack at a high temporal resolution and thus demonstrates its great potential. Also, the inferred SWE measurements lie within the uncertainty of manual observations. Furthermore, the µ-CRSG has several advantages over the n-CRSG; It is cheaper, lighter and promises a higher measurement precision due to the improved counting statistics of the muon count rates. We conclude that the µ-CRSG has even greater potential than the n-CRSG to monitor SWE in remote high mountain environments.

How to cite: Gugerli, R., Desilets, D., and Salzmann, N.: Application of cosmic ray snow gauges to monitor the snow water equivalent on alpine glaciers , EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1002, https://doi.org/10.5194/egusphere-egu22-1002, 2022.

08:42–08:48
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EGU22-10269
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Virtual presentation
Advances in X- and Ku- Band Radar Algorithms for SWE Retrieval
(withdrawn)
Edward Kim et al.
08:48–08:54
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EGU22-3205
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ECS
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Highlight
Mathieu Le Breton et al.

Estimation of snow SWE using passive RFID tags as radar reflectors

Mathieu Le Breton(1,2), Éric Larose(1), Laurent Baillet(1), Alec van Herwijnen(3), Yves Lejeune(4)

(1) Univ. Grenoble Alpes, CNRS, ISTerre, Grenoble, France
(2)
Géolithe Innov, Géolithe, Crolles, France
(3)
WSL Institute for Snow and Avalanche Research SLF, Davos, Switzerland
(4)
CEN-CNRM, Météo-France, CNRS, Saint Martin d’Heres, France

 

Passive radio-frequency identification (RFID) tags are used massively to remotely identify industrial goods, and their capabilities offer new ways to monitor the earth’s surface already applied to coarse sediments, landslides, rock fissures and soils (Le Breton et al., 2910, 2020, 2021b). We introduce a method to estimate the variations in snow water equivalent (SWE) of a snowpack using an 865–868 MHz (RFID) system based on commercial off-the-shelf devices. The system consists of a vertical profile of low-cost passive tags installed before the first snowfall, on a structure that is minimally disruptive to the snowpack. The tags are interrogated continuously and remotely by a fixed reader located above the snow. The key measured value is the increase of phase delay, induced by the new layers of fresh snow which slow down the propagation of the waves. The method is tested both in a controlled laboratory environment, and outdoors on the Col de Porte observation site, in order to cross-check the results with a well-documented reference dataset (Lejeune et al., 2019). The experiments demonstrate that SWE can be estimated by this non-contact and non-destructive RFID technique. However, multipath interferences in the snowpack can generate errors up to 40 mm of SWE. This error is mitigated by using multiple tags and antennas placed at different locations, allowing the RFID measurements to remain within +/-10% of the cumulated precipitations (outdoor) and snow weighting (laboratory). In complement, the system can also estimate whether the snow is wet or dry, using temperature sensors embedded in the tags combined with the received signal strength. Using this approach with a mobile reader could allow the non-destructive monitoring of snow properties with a large number of low-cost, passive sensing tags.

 

Publications related to the project:

Le Breton, M., Baillet, L., Larose, E., Rey, E., Benech, P., Jongmans, D., Guyoton, F., Jaboyedoff, M., 2019. Passive radio-frequency identification ranging, a dense and weather-robust technique for landslide displacement monitoring. Eng. Geol. 250, 1–10. http://doi.org/10.1016/j.enggeo.2018.12.027

Le Breton, M., Grunbaum, N., Baillet, L., Larose, É., 2021a. Monitoring rock displacement threshold with 1-bit sensing passive RFID tag (No. EGU21-15305). Presented at the EGU21, Copernicus Meetings. http://doi.org/10.5194/egusphere-egu21-15305

Le Breton, M., Liébault, F., Baillet, L., Charléty, A., Larose, É., Tedjini, S., 2021b. Dense and long-term monitoring of Earth surface processes with passive RFID -- a review. Submitted. Preprint at: https://arxiv.org/abs/2112.11965v1

Lejeune, Y., Dumont, M., Panel, J.-M., Lafaysse, M., Lapalus, P., Le Gac, E., Lesaffre, B., Morin, S., 2019. 57 years (1960–2017) of snow and meteorological observations from a mid-altitude mountain site (Col de Porte, France, 1325 m of altitude). Earth Syst. Sci. Data 11, 71–88. http://doi.org/10.5194/essd-11-71-2019

How to cite: Le Breton, M., Larose, É., Baillet, L., van Herwijnen, A., and Lejeune, Y.: Estimation of snow SWE using passive RFID tags as radar reflectors, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3205, https://doi.org/10.5194/egusphere-egu22-3205, 2022.

08:54–09:00
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EGU22-12490
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ECS
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On-site presentation
Aitor Orio et al.

The seasonal snowpack influences the hydrology, ecology and economy of the areas where it is present. However, the real time monitoring of the seasonal snowpack is a still well known scientific challenge. In this study, we have explored the potential of muon scattering radiography (MSR) to infer the snow water equivalent (SWE) of the snowpack. We have used the energy and mass balance model Snowpack to realistically simulate the time evolution and microstructure of the snowpack. The ERA5-Land reanalysis was used as forcing of Snowpack, in a location close to the Monte Perdido massif (Central, Pyrenees) at an elevation of 2041m above sea level. The simulations cover the hydrologic year 2015/2016, approximately reaching up to 700mm of peak SWE. Then, we have coupled the Snowpack numerical simulations with the Geant4 model to simulate the propagation of the muons through the snow layers and to collect the deviation of the muon trajectories. We have measured these deviations with a virtual muon detector based in multiwire proportional chambers, replicating a real detection system designed by us. The obtained distributions of muon deviations have exhibited a strong correlation with the simulated SWE, showing a coefficient of determination of 0.99. This model presents a root-mean-square error (RMSE) of 23.9mm in the SWE estimation. In order to validate the simulation analysis results, we have replicated the numerical experiments under controlled conditions, measuring three artificial snow samples ranging from 0 to 200 mm of SWE in our laboratory. We have measured the samples with an experimental setup composed of the real muon detector whose hardware was virtually replicated for the numerical experiments. Then, we have applied the model derived from the numerical simulations to the muon deviations measured in our laboratory. We have calibrated the real measurements and we have obtained a RMSE of 38.4mm in the SWE estimation. These results show that MSR is a promising non-destructive technique that can be used for the deployment of accurate SWE monitoring networks and can eventually provide information from the internal layered structure of the snowpack.

How to cite: Orio, A., Alonso, E., Martínez, P., Díez, C., and Gómez, P.: Exploring the potential of cosmic muon scattering to measure the snow water equivalent, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12490, https://doi.org/10.5194/egusphere-egu22-12490, 2022.

09:00–09:06
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EGU22-4573
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ECS
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Virtual presentation
Giulia Graldi et al.

Ground and space based GNSS-IR (Interferometric Reflectometry) has been used in the last 20 years for characterizing the Earth Surface, together with other remote sensing techniques. Among the physical quantities which can be monitored using these techniques, the characterization of the snow cover is of particular interest since it is an important source of freshwater. The increase of the global temperature due to anthropogenic climate changes is threatening the seasonal recharging, and for this reason monitoring the snow cover is crucial. Ground based GNSS-IR can be used for obtaining information on the height of the snowpack, with a precision of 0.04 m by using geodetic-grade GNSS instruments (such those involved in Continuously Operating Reference Stations - CORS). In the present study, the sensitivity of the retrieval of the snowpack height from data acquired with low cost non-geodetic grade instruments with the GNSS-IR technique is evaluated. The analysis is applied to a flat alpine area in the Lavarone plateau in the Province of Trento, Italy (1400 m above sea level), where GNSS field campaigns were carried out in 2018, 2019 for short time periods (90, 120 minutes) due to constraints of the study area. Single-frequency GPS observations were collected with u-blox M8T GNSS receivers and patch u-blox and Tallysman antennas. Leica antenna and receiver were also used for collecting GPS data in double frequency, in order to acquire reference data with geodetic grade instruments. Given the characteristics of the area, it is possible to consider that GPS signals reflect with specular reflection, and thus modelling the Signal to Noise Ratio (SNR) as a function of the distance between the reflecting snow surface above solid ground and the antenna. Multipath frequency associated with snowpack height is retrieved by applying the Lomb Scargle Periodogram on SNR data. The results show that, by applying GNSS-IR technique to data acquired with low-cost receivers and antennas, it is possible to retrieve the height of the snow pack with a standard deviation of about 0.05 m. This demonstrates the feasibility of GNSS-IR also with non-geodetic grade instruments.

How to cite: Graldi, G., Rover, S., and Vitti, A.: Single-frequency GNSS-IR for estimating snowpack height with consumer grade receivers and antennas, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4573, https://doi.org/10.5194/egusphere-egu22-4573, 2022.

09:06–09:12
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EGU22-12082
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ECS
Edoardo Raparelli et al.

The Apennine mountain range is the backbone of the Italian peninsula, crossing it from North-West to South-East for approximately 1200 km. The main peaks are found in Central Apennines, especially in the Gran Sasso d’Italia massif, which hosts the highest Apennines peak, named Corno Grande, with its 2912 m a.s.l. During the winter season, Central Apennines are typically covered with snow, with thickness that can vary between a few centimeters to several meters. Despite the historical presence of snow in these territories, the Apennine snowpack is poorly studied and weather data coming from automatic measurement stations and manual snow measurements hardly coexist. Thus, within the SMIVIA (Snow-mantle Modeling, Inversion and Validation using multi-frequency multi-mission InSAR in Central Apennines) project, we identified the measurement sites of Pietrattina, at 1459 m a.s.l, and Campo Felice, at 1545 m a.s.l., both located in Central Apennines. There we collected automatic measurements using ad hoc installed automatic weather-snow stations (AWSS) and where we performed systematic manual measurements of the snowpack properties, from November 2020 till April 2021. The AWSS measures every 5 minutes air temperature, relative humidity, wind speed, wind direction, incoming short-wave radiation, reflected short-wave radiation, soil surface temperature, snow surface temperature and snow height. The manual part of the campaign included the digging of 10 and 8 snow pits at Pietrattina and Campo Felice sites, respectively, to measure vertical profiles of snow density, temperature, grain shape, grain size and fractional content of light absorbing impurities. Manual snow measurements provide important information on the state of the snowpack, and give the opportunity to reconstruct the history of the snowpack. Their proximity to automatic weather stations let us evaluate the impact of the very local atmospheric conditions on the snowpack evolution. These measurements were performed within the SMIVIA project to: i) evaluate the ability of the snow cover model SNOWPACK to reproduce the observed snow cover properties; ii) verify the possibility to infer snow height and snow water equivalent from the data retrieved with Earth observation satellites; iii) investigate whether the use of a combination of snow numerical models and remote sensing data may provide better results compared to using each of the aforementioned approach, separately. Nevertheless, the data collected during the SMIVIA campaign at the measurement sites of Pietrattina and Campo Felice during season 2020-2021 can also provide precious information for other fields of study, like hydrology, biology and chemistry.

How to cite: Raparelli, E., Tuccella, P., Lombardi, A., Palermo, G., Alvan Romero, N., Papa, M., Picciotti, E., Di Fabio, S., Pettinelli, E., Mattei, E., Lauro, S., Cosciotti, B., Petroselli, C., Cappelletti, D., Pecci, M., and Marzano, F. S.: Snow measurement campaign for snowpack model and satellite retrieval validation in Italian Central Apennines within SMIVIA project, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12082, https://doi.org/10.5194/egusphere-egu22-12082, 2022.

09:12–09:18
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EGU22-3248
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Virtual presentation
Jesús Revuelto et al.

In the Pyrenees, as in other mid latitude mountain ranges, sub alpine areas have a long lasting snow cover that affect different mountain processes, including river discharge timing, soil erosion, primary production or animal and plant phenology. This work presents and analyzes a complete snow depth and Normalized Difference Vegetation Index (NDVI) spatial distribution dataset, generated by Unmanned Aerial Vehicles (UAV) over two years. This study aims to increase the knowledge and understanding of the relationship of the duration and timing of snowmelt and vegetation cover and its annual cycle.

The dataset was obtained in Izas Experimental Catchment, a 55 ha study area located in Central Spanish Pyrenees ranging between 2000 to 2300 m a.s.l., which is mostly covered by grasslands. A total of 18 UAV snow depth and 14 NDVI observations were obtained by a fixed wing UAV equipped with RGB and multispectral cameras during 2020 and 2021. The melt out date for the different areas of the catchment has been obtained from the snow depth distribution dataset, which in turn has been used to analyze the NDVI evolution. The NDVI values for each UAV flight have been correlated with the snow depth distribution observed in previous dates and with different topographic variables as elevation, solar radiation, curvature (through the Topographic Position Index) or slope.

The maximum seasonal NDVI happens throughout the study area simultaneously in the entire study area; however those zones with the latest snow disappearance do not reach NDVI values as high as those observed in areas with earlier snow disappearance. Oppositely areas with the soonest snow melting (in late February) have lower maximum NDVI values that those observed in areas with snow melting occurring later (around May).  NDVI correlations have shown that the snow depth distribution observed about one month prior to each NDVI acquisition has a very important control on pasture phenology. This correlation is particularly evident on the free-snow areas during first melting weeks, with a lower influence in those areas where snow melts at the end of the snow season. This field study exemplifies how intensive UAV acquisitions allow understanding snow processes over extended areas with an unprecedented spatial resolution.

How to cite: Revuelto, J., Sobrino, J., Gómez, D., Rodriguez-López, G., Alonso-González, E., Rojas-Heredia, F., Izagirre, E., Montorio-Lloveria, R., Pérez-Cabello, F., and López-Moreno, J. I.: Annual development of subalpine grassland observed with UAV: how NDVI evolution is controlled by snow melting, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3248, https://doi.org/10.5194/egusphere-egu22-3248, 2022.

09:18–09:24
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EGU22-10835
Wolfgang Rack et al.

Snow on sea ice is a controlling factor for ocean-atmosphere heat flux and thus ice thickness growth, and surface albedo. Active and passive microwave remote sensing is the most promising way to estimate snow depths over large sea ice areas although improved validation is understood as a missing information to support further progress. However, severe limitations in the representative measurement of snow depth over sea ice persist, which exacerbates sea ice mass balance assessments as well as the indirect estimation of consolidated ice thickness from remotely sensed freeboard.

We have designed and flown a snow radar in combination with an electromagnetic induction device for sea ice thickness. The goal was the simultaneous measurement of both the consolidated sea ice thickness and the snow depth on top as a tool to derive snow and ice statistics for satellite validation. The snow radar was integrated into an EM-bird and flown about 15 m above the surface by suspending the instrument from a helicopter. The combination of the applied technologies hasn’t been deployed in this configuration before. The helicopter flight speed was around 70 knots, resulting in a snow measurement about every four meters. The EM instrument can detect ice thickness at 0.1m accuracy, whereas the snow radar is designed to measure snow depth at 0.05m accuracy.

Our field area was the land-fast sea ice and adjacent ice shelf in McMurdo Sound (Antarctica) in November 2021. During this time we found a relatively shallow but variable snow cover (up to about 0.3m) above sea ice of about 2m thickness. Deeper snow was only measured at the transition from the sea ice to the ice shelf, and on the ice shelf itself, where the maximum radar penetration in snow in ideal conditions is estimated to be around 2-3 meters.

We present first results of snow cover statistics in comparison to ground validation and observed snow characteristics, and we compare these results to airphotos and optical satellite imagery. We show that the measurement set-up meets the requirements for level ice and rough fast ice with patchy but dry snow cover. The system still needs to be tested over pack ice with potentially more complex snow morphology.

How to cite: Rack, W., Tan, A., Haas, C., Farooq, U., Taylor, A., Kind, A., Barnsdale, K., and Leonard, G.: Combined measurement of snow depth and sea ice thickness by helicopter EM bird in McMurdo Sound, Antarctica, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10835, https://doi.org/10.5194/egusphere-egu22-10835, 2022.

09:24–09:30
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EGU22-3030
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On-site presentation
Maximilian Semmling et al.

Sea ice is a crucial parameter of the Earth’s climate system. Its high albedo compared to water and its insulating effect between ocean and atmosphere influences the oceans’ radiation budget significantly. The importance of monitoring sea-ice properties arises from the high variability of sea ice induced by seasonal change and global warming. GNSS reflectometry can contribute to global monitoring of sea ice with high potential to extend the spatio-temporal coverage of today’s observation techniques. Properties like ice salinity, temperature, thickness and snow cover can affect the signal reflection. The MOSAiC expedition (Multidisciplinary drifting Observatory for the Study of Arctic Climate) gave us the opportunity to conduct reflectometry measurements under different sea-ice conditions in the central Arctic. A dedicated setup was mounted, in close cooperation with the Alfred-Wegener-Institute (AWI), on the German research icebreaker Polarstern that drifted for one year with the Arctic sea ice.

We present results from data recorded between autumn 2019 and spring 2020. The ship drifted in this period from the Siberian Sector of the Arctic (October 2019), over the central Arctic (November 2019 until May 2020) towards Fram Strait and Svalbard (reached in June 2020). Profiles of sea-ice reflectivity over elevation angle (range: 1° to 45°) are derived with daily resolution considering reflection data recorded at left-handed (LH) and right-handed (RH) circular polarization. Respective predictions of reflectivity are based on reflection models of bulk sea ice or a sea-ice slab. The latter allows to include the effect of signal penetration down to the underlying water. Results of comparison between LH profiles and bulk model confirm a reflectivity decrease (about 10 dB) when surrounding open water areas is reduced (by freezing) and the ship drifts in compact sea ice.

Further results comprise estimates of sea-ice permittivity from mid-elevation range reflectivity (10° to 30°). The median of estimated permittivity 2.4 (period of compact sea ice) lies in the expected range of reported old ice type (mostly second-year ice). The retrieved reflectivity in the low-elevation range (1° to 10°) give strong indication of signal penetration into the dominating second-year ice with influence of sea ice temperature and thickness. We conclude that sea-ice characterization in future can profit form GNSS reflectometry observations. The on-going study is currently extended to the further evolution of Arctic sea ice during winter and spring period of the MOSAiC expedition.

How to cite: Semmling, M., Wickert, J., Kreß, F., Hoque, M., Divine, D., Gerland, S., and Spreen, G.: Arctic Sea-Ice Permittivity Derived from GNSS Reflectometry Data of the MOSAiC Expedition , EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3030, https://doi.org/10.5194/egusphere-egu22-3030, 2022.

09:30–09:36
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EGU22-7154
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ECS
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On-site presentation
Frederieke Miesner et al.

The thermal regime under lakes, ponds, and shallow near shore zones in permafrost zones in the Arctic is predominantly determined by the temperature of the overlying water body throughout the year.   Where the temperatures of the water are warmer than the air, unfrozen zones within the permafrost, called taliks, can form below the water bodies.

However, the presence of bottom-fast ice can decrease the mean annual bed temperature in shallow water bodies and significantly slow down the thawing or even refreeze the lake or sea bed in winter. Small changes in water level have the potential to drastically alter the sub-bed thermal regime between permafrost-thawing and permafrost-forming. The temperature regime of lake sediments is a determining factor in the microbial activity that makes their taliks hot spots of methane gas emission. Measurements of the sediment temperature below shallow water bodies are scarce, and single temperature-chains in boreholes are not sufficient to map spatial variability.

We present a new device to measure in-situ temperature-depth profiles in saturated soils or sediments, adapting the functionality of classic Bullard-type heat flow probes to the special requirements of the Arctic. The measurement setup consists of 30 equally spaced (5cm) digital temperature sensors housed in a 1.5 m stainless steel lance. The lance is portable and can be pushed into the sediment by hand either from a wading position, a small boat or through a hole in the ice during the winter. Measurements are taken continuously and 15 minutes in the sediment are sufficient to acquire in-situ temperatures within the accuracy of the sensors (0.01K after calibration at 0°C). The spacing of the sensors yield a detailed temperature-depth-profile of the near-surface sediments, where small-scale changes in the bottom water changes dominate the temperature field of the sediment. The short time needed for a single measurement allows for fine-meshed surveys of the sediment in areas of interest, such as the transition zone from bottom-fast to free water.

 

Test campaigns in the Canadian Arctic and on Svalbard have proven  the device to be robust in a range of environments. We present data acquired during winter and summer, covering non-permafrost, thermokarst lake and offshore measurements.

How to cite: Miesner, F., Cable, W., Boike, J., and Overduin, P. P.: In-situ measurements of sediment temperature under shallow water bodies in Arctic environments, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7154, https://doi.org/10.5194/egusphere-egu22-7154, 2022.

09:36–09:42
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EGU22-12233
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Highlight
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Virtual presentation
Cedric Schmelzbach et al.

Seismic 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. Seismic data can provide an alternative to remote-sensing and ground-based radar measurements for estimation of ice thickness in cases where radar techniques fail. Because of the difficult access to Alpine and Arctic environments as well as seismic sensor coupling issues in ice environments, it is of interest to optimize the use of seismic instruments in terms of sensor type, sensor numbers and layouts.

With the motivation to monitor over time the seismic activity of the lake ice and the ice properties, we conducted a series of seismic experiments on frozen lake St. Moritz in the Swiss Alps during two consecutive winters. Arrangements of sensors ranging in numbers from 96 geophones in mini-arrays to installations of 8, 2 and 1 conventional seismic sensors were used to measure the seismic wavefield generated by ice quakes (cryoseisms), artificial sources like hammer strokes, and ambient vibrations. These data provide an impressive and rich insights into the growth of the ice and variations of seismic activity with time. Even recordings with only a single station enable the determination of ice parameters and location of ice seismicity. Furthermore, we are exploring the value of recording air-coupled waves with microphones as alternative contact-free measurements related to seismic wave propagation in the ice, possibly even with sensors placed on the lake shore.

How to cite: Schmelzbach, C., May, D., Wetter, C., Stähler, S., and Clinton, J.: Monitoring lake ice with seismic and acoustic sensors, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12233, https://doi.org/10.5194/egusphere-egu22-12233, 2022.

09:42–10:00
Discussion Session Block 1

Wed, 25 May, 10:20–11:50

Chairpersons: Emma C. Smith, Winnie Chu

10:20–10:26
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EGU22-574
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ECS
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On-site presentation
Fabian Becker et al.

We will present the design of a permittivity sensor that can be attached to a melting probe and measure the respective ice properties during the melting process, yielding in a comprehensive permittivity profile. Melting probes were already successfully applied in terrestrial cryospheres, such as alpine glaciers and Antarctica. Further applications to cross the ice shield on Dome C in Antarctica or even on icy moons in the outer solar system, such as Europa, are already planned e.g. within the TRIPLE project line funded by the German aerospace center. A sensor measuring the permittivity of the surrounding ice in situ during melting could provide valuable data about the ice properties. The respective density of the ice is correlated with the permittivity, or volcanic ash layers can be identified through permittivity measurements. Another usage of the data could be to correct distance measurements from radar travel times within the ice.

The sensor is designed to operate in the frequency range of 0.1 - 1.5 GHz and works in the range of the near field, which is defined to be within one wavelength, corresponding to the frequency. The concept of this sensor is based on an open coaxial probe, which is connected to the medium of interest. The measurement principle and calibration techniques, as well as first lab measurement results of ice and other materials will be presented. A comprehensive data set on effects of porosity, salinity and impurities of lab-manufactured ice samples on the permittivity will also be given. These data will help to interpret the taken permittivity profiles of glaciers on further missions.

We will also show how the device can be integrated into a melting probe, such as the TRIPLE melting probe. One major challenge is to ensure good contact to the ice during measurement. The diameter of a melting hole often results to be several cm larger in diameter than the melting probe itself. A mechanism that extends the sensors of the melting probe and press it onto the ice for measurements is being developed. 

How to cite: Becker, F., Friend, P., and Helbing, K.: Development of a permittivity sensor for melting probes to explore terrestrial and extraterrestrial cryospheres, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-574, https://doi.org/10.5194/egusphere-egu22-574, 2022.

10:26–10:32
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EGU22-10195
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ECS
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On-site presentation
Marc S. Boxberg et al.

Several icy moons of our Solar System like Jupiter’s moon Europa have a global ocean of liquid water below their icy crust. These ocean worlds are possible targets for space missions that aim to assess their potential for habitability or even to search for life. Cryobots (or ice melting probes) are suitable tools to reach the subglacial oceans for in-situ investigations. The necessary ice shell transit provides an excellent opportunity to investigate structure and composition of the ice itself by means of geophysical and other in-situ measurements. This will allow us to better understand the evolution of icy moons and their role in our solar system.

We present current ideas as well as first results from terrestrial analogue studies. Acoustic data obtained during a field test on Langenferner Glacier, Italy was used to conduct a travel time tomography, which yields insight into heterogeneities in the local acoustic wave propagation speed through the ice. The acoustic sensor set-up was originally designed for localization of the melting probe rather than an investigation of the ice structure. However, we can still show that such opportunity data can be used to obtain a wave velocity distribution which can be further interpreted with respect to ice properties like porosity.

While we already investigated the acoustic data, we evaluate the potential of other measurements. For example, Radar measurements in combination with the acoustics can be used to identify the ice-water boundary and, in addition, cracks and inclusions in the ice. Conductivity measurements provide information on the salinity. At ice-water interface regions, the salinity is in thermochemical equilibrium with the temperature and porosity of the ice. We present our concept for on-board electrical conductivity measurements and analyze its potential, for example, to constrain ice properties and to predict ice-water interfaces based on existing terrestrial field data and process models. Furthermore, some of the cryobot’s housekeeping data might be of interest for investigating the ambiance, too. For example, the temperature and the density of the ice affect the melting velocity of the cryobot, which constitutes an inverse problem to get further information on the ice.

How to cite: Boxberg, M. S., Simson, A., Chen, Q., and Kowalski, J.: Investigation of ice with geophysical measurements during the transit of cryobots, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10195, https://doi.org/10.5194/egusphere-egu22-10195, 2022.

10:32–10:38
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EGU22-612
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ECS
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Highlight
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On-site presentation
Anja Rutishauser et al.

In recent decades, the Greenland Ice Sheet (GrIS) has experienced a significant increase in surface melting and meltwater runoff, which is now the main contributor to GrIS mass loss. In areas covered by firn, meltwater percolation and refreezing processes can significantly buffer meltwater runoff to the ocean. However, this process leads to the formation of ice layers and an overall firn densification, which is predicted to limit the firns’ meltwater storage capacity in the future. Additionally, the high spatial and temporal variability of ice layer formation and subsequent firn densification can cause large uncertainties in altimetry-derived mass balance estimates. Thus, understanding the spatial and vertical extent of ice layers in the firn is important to estimate the GrIS contribution to sea-level rise.

Due to limited direct observations of firn properties, modeling future meltwater runoff and processes over the rapidly changing GrIS firn facies remains challenging. Here, we present a prospective new technique that leverages concurrent airborne radar sounding and laser altimetry measurements to characterize near-surface firn over spatially extensive areas. We hypothesize that due to their different depth sensitivities, the presence of ice layers in the firn yields an offset between radar sounding- and laser-derived surface elevations (differential altimetry). We compare existing airborne radar and laser measurements to in-situ firn observations and use one-dimensional radar sounding simulations to investigate 1) the sensitivity of the differential altimetry technique to different firn facies, and 2) the techniques’ capability to estimate firn density and firn ice content. Preliminary results over the western GrIS show good correlations between differential altimetry signatures and areas of firn affected by percolation and refreezing processes.

Through this technique, we explore the potential to leverage a wealth of radar sounding measurements conducted at low frequencies (< 200 MHz), that typically do not resolve the firn structure, to derive near-surface firn properties. Finally, we apply the differential altimetry technique to data collected as part of NASA’s Operation IceBridge between 2009-2019 to derive spatio-temporal changes in the GrIS firn in response to climatic conditions, in particular the formation of ice layers and changes in firn ice content. Our results can help reduce uncertainties in satellite-derived mass balance measurements and improve firn models, which both contribute to reducing uncertainties in current and projected GrIS contributions to global sea-level rise.

How to cite: Rutishauser, A., Ahlstrøm, A. P., Fausto, R. S., Karlsson, N. B., Vandecrux, B., Scanlan, K. M., Picard, G., and Andersen, S. B.: Using offsets in airborne radar sounding and laser altimetry to characterize near-surface firn properties over the Greenland ice sheet, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-612, https://doi.org/10.5194/egusphere-egu22-612, 2022.

10:38–10:44
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EGU22-6414
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ECS
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On-site presentation
Kristian Chan et al.

Atmospheric warming has led to increased surface melting on glaciers in the Arctic. This meltwater can percolate into firn and refreeze to form ice layers. Depending on their thickness, low-permeability ice layers can act as barriers that inhibit subsequent vertical meltwater infiltration in deeper firn pore space and favor lateral meltwater runoff. Thus, characterizing ice layers in firn is key for understanding the near-surface hydrological conditions that could promote surface meltwater runoff and its contribution to sea level rise.

Airborne ice-penetrating radar (IPR) is a powerful tool for imaging subsurface structure, but only recently have these systems been applied to direct observations of the bulk properties of the near-surface. To evaluate the bulk permeability of the near-surface firn system of Devon Ice Cap (DIC), Canadian Arctic, we use the Radar Statistical Reconnaissance (RSR) technique, originally developed for accumulation studies in West Antarctica. This method utilizes both the coherent and incoherent components of the total surface return, which are predominately sensitive to near-surface permittivity/structure within the system’s vertical range resolution and surface roughness, respectively. Here, we apply RSR to IPR data collected over DIC with the High-Capability Airborne Radar Sounder 2 (HiCARS) system (60 MHz center-frequency, 15 MHz bandwidth), operated by the University of Texas Institute for Geophysics (UTIG). Guided by ground-based ice-penetrating radar data and firn core density measurements, we show that the near-surface heterogeneous firn structure, featuring ice layers, mainly affects the observed coherent component.

We further compare the coherent component of HiCARS with that derived from IPR data collected with the University of Kansas Multichannel Coherent Radar Depth Sounder (MCoRDS) 3 system (195 MHz center-frequency; 30 MHz bandwidth), to evaluate the utility of dual-frequency IPR for characterizing near-surface ice layers. We expect that each radar system is sensitive to a different scale of near-surface bulk properties (i.e., depth and thickness of ice layers of different vertical extents), governed by each radar systems’ center frequency and bandwidth-limited range resolution. We leverage these differences in range resolution to derive ice layer thickness constraints in the DIC firn zone containing meter-thick ice layers, which are consistent with ground-based observations. Our results suggest this dual-frequency approach does indeed show that ice layers are vertically resolvable, spatially extensive, and mostly impermeable to surface meltwater. Thus, we hypothesize that lateral flow over high elevation meter-thick ice layers may contribute to the total surface runoff routed through supraglacial rivers down-glacier in the ablation zone.

How to cite: Chan, K., Grima, C., Rutishauser, A., Young, D. A., Culberg, R., and Blankenship, D. D.: Ice layer detection, distribution, and thickness in the near-surface firn on Devon Ice Cap: a new dual-frequency radar characterization approach, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6414, https://doi.org/10.5194/egusphere-egu22-6414, 2022.

10:44–10:50
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EGU22-7409
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ECS
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Virtual presentation
Wen Zhou et al.

Measurements of the seismic properties of Antarctic ice streams are critical for constraining glacier dynamics and future sea-level rise contributions. In 2020, passive seismic data were acquired at the Rutford Ice Stream, West Antarctica, with the aim of imaging the near-surface firn layer. A DAS (distributed acoustic sensing) interrogator and 1 km of optic fibre were supplemented by 3-component geophones. Taking advantage of transient seismic energy from a petrol generator and seismicity near the ice stream shear margin (10s of km away from the DAS array), which dominated the ambient seismic noise field,  we retrieve Rayleigh wave signals from 3 to 50 Hz. The extracted dispersion curve for a linear fibre array shows excellent agreement with an active seismic surface wave survey (Multichannel Analysis of Surface Waves) but with lower frequency content. We invert the dispersion curves for a 1D S-wave velocity profile through the firn layer, which shows good agreement with the previously acquired seismic refraction survey. Using a triangular-array geometry we repeat the procedure and find no evidence of seismic anisotropy at our study site. Our study presents challenges and solutions for processing noisy but densely sampled DAS data, for noise interferometry and imaging. 

How to cite: Zhou, W., Butcher, A., Kendall, J. M., Kufner, S.-K., and Brisbourne, A.: S-wave velocity profile of an Antarctic ice stream firn layer with ambient seismic recording using Distributed Acoustic Sensing, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7409, https://doi.org/10.5194/egusphere-egu22-7409, 2022.

10:50–10:56
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EGU22-942
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On-site presentation
Reinhard Drews et al.

The internal ice stratigraphy as imaged by radar is an integrated archive of the atmospheric- oceanographic, and ice-dynamic history that the ice sheet has experienced. It provides an observational constraint for ice flow modeling that has been used for instance to predict age-depth relationships at prospective ice-coring sites in Antarctica’s interior. The stratigraphy is typically more disturbed and more difficult to image in coastal regions due to faster ice flow. Yet, knowledge of ice stratigraphy across ice shelf grounding lines and further seawards is important to help constrain ocean-induced melting and associated stability.

Here, we present preliminary results of synthesizing information from radar stratigraphic characteristics from airborne and ground-based radar surveys that have been collected for specific projects starting from the 1990s onwards focusing on ice marginal zones of Antarctica. The key data is based on airborne surveys from the German Alfred Wegener Institute’s polar aircrafts equipped with a 150 MHz radar. In the meantime this system has been replaced by an ultra-wide band 150-520 MHz radar. The older data will provide a baseline with extensive coverage that can be used for model calibration and change detection over time. We aim to provide metrics of the radio stratigraphy (e.g. shape and slope of internal reflection horizons) as well as classified prevalent stratigraphy types that can be used to calibrate machine learning approaches such as simulation based inference. The data obtained will be integrated in coordination efforts within the SCAR AntArchitecture Action Group.

How to cite: Drews, R., Koch, I., Oraschewski, F., Ershadi, M., Muhle, L. S., Spiegel, H., Visnjevic, V., Moss, G., Macke, J., Franke, S., Jansen, D., Steinhage, D., and Eisen, O.: Towards assembling the internal ice stratigraphy in coastal regions of Dronning Maud Land, East Antarctica, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-942, https://doi.org/10.5194/egusphere-egu22-942, 2022.

10:56–11:02
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EGU22-4934
Climatic imprint in the mechanical properties of ice sheets and its effect on ice flow. Observations from South Pole and EPICA Dome C ice cores
(withdrawn)
Carlos Martin et al.
11:02–11:08
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EGU22-7758
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ECS
Stress coupling between supraglacial lakes during rapid drainage
(withdrawn)
Laura A. Stevens et al.
11:08–11:14
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EGU22-1021
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On-site presentation
Olaf Eisen et al.

In recent years radar polarimetry has re-surfaced as an ideal tool to determine ice-fabric patterns and linked mechanical ice anisotropy. The leap forward was facilitated by coherent data processing often collected by phase-sensitive Radio-Echo-Sounding (pRES) systems at fixed locations. The polarimetric response can either be synthesized from a set of quad-polarimetric measurements or obtained by manually rotating the antennas. Specifics of the data collection in the field varied between the different surveys, and no set of best practices has yet emerged.  Here we present a systematic study that includes more than fifty different combinations of how polarimetric data can be acquired, including:

  • different distances between the transmitter and receiver (2, 4 and 8 m)
  • different combinations in polarization orientation (22.5 deg)
  • a comparison between discrete full azimuthal data collected every 22.5 degrees and synthesized data collected in a quad-pole setup
  • the effect of 180-degree polarization orientation on repeat measurements, e.g., basal melt rate and polarimetric analysis, e.g., coherence phase
  • definition of Horizontal (H) and Vertical (V) orientation is pRES antenna setup and its impact on synthesizing and analyzing data
  • 90-degree fabric orientation ambiguity in polarimetric data

This study aims to provide best practices, considering that observation time in the field is limited. Ideally, this will lead to a unified setup and nomenclature, facilitating better compatibility from data collected by different groups on ice sheets, shelves, and glaciers.

How to cite: Eisen, O., Ershadi, R., Drews, R., Berger, S., Gong, D., Li, Y., Martin, C., and Zeising, O.: Best practices for collecting polarimetric data with ApRES for constraining ice-fabric orientation and its spatial variability, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1021, https://doi.org/10.5194/egusphere-egu22-1021, 2022.

11:14–11:20
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EGU22-6377
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ECS
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Virtual presentation
Sheng Dong et al.

The radar detection of bedrock interface and internal ice layers is a widely used technique for observing interiors and bottoms of ice sheets, which is also an important indicator of inferring the evolution of glaciers and explaining subglacial topographies. The conventional methods, such as the filtering denoise, are limited by the low contrast in ice radar image with noise and interferes and thus the automatic method in tracing and extracting layers' features is trapped. The manual and semiautomatic methods are widely applied but with large time-consuming especially for the large-scale radar image with continuous bedrock and internal layers. To extract and identify the bedrock interface and internal ice layers automatically, we propose EisNet, a fusion system consisting of three sub neural networks. Because of the limitations of conventional manual methods, it is relatively rare that the high-precision extraction of layer features, which can be applied as labels in training. To obtain sufficient radar images with high-quality training labels, we also propose a novel synthetic method to simulate the not only visual texture of the bedrock interface and internal layers but also the artifact noise and interference to match the feature in field data. EisNet is first verified on synthetic data and shows capacity on the extraction of multi types of layer targets. Second, the application on observational radar images reveals EisNet’s generalized performance from synthetic data to the CHINARE data. EisNet is also applied to extract bedrock interfaces from the radar film from the Antarctic. EisNet is now open open-accessing. We hope that EisNet could be applied in more ice radar images from other regions and different forms to promote glacial research.

How to cite: Dong, S., Tang, X., and Fu, L.: Using EisNet to Extract Bedrock and Internal layers from Digital and Analog Radiostratigraphy in Ice Sheets , EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6377, https://doi.org/10.5194/egusphere-egu22-6377, 2022.

11:20–11:26
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EGU22-5506
Duncan Young et al.

Ice thickness is a key parameter for predictive ice sheet modeling, geological interpretation of the underlying bed rock, and site selection for deep ice sheet and bed rock sampling.  However, the uncertainties typically reported are in terms of crossover statistics, and ice thickness uncertainties are generally not formally integrated into ice sheet models.  Here we examine what crossover statistics reveal and conceal for the actual uncertainty in reported ice thickness, examine the impact of system and geometric parameters on uncertainties, and place these parameters in the context of the observed subglacial roughness.  We provide a predictive model for uncertainties as a function of ice thickness, sensor height, and subglacial roughness parameters, evaluate it from the perspective of ground based, airborne and orbital sounding and make recommendations for parameters that should be reported in ice thickness data products.

How to cite: Young, D., Kempf, S., and Ng, G.: Beyond crossovers: Predicting ice thickness uncertainties in ice penetrating radar data from geometric controls, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5506, https://doi.org/10.5194/egusphere-egu22-5506, 2022.

11:26–11:32
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EGU22-12006
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Virtual presentation
Glenn Jones et al.

The physical properties of the ice column are fundamental to the deformation and flow of glaciers and ice sheets. With a warming climate, surface meltwater is ever increasingly being routed and distributed throughout the ice column changing the mechanical and hence thermal properties of the ice and leading to accelerated ice flow and ice mass loss. Since the early 1990s, ice mass loss from the Greenland Ice Sheet (GrIS) has contributed ~10% of the mean global sea level rise. Seismic waves have routinely been used to study the physical characteristics of glaciers and ice sheets due to their sensitivity to both mechanical and thermal properties of ice. Traditionally, reflection seismic surveys have been chosen as the primary seismic approach but this survey method can suffer from difficult logistics in polar regions. Recent advancements in ambient noise methods and the permanent installation of a seismic network in Greenland now permit the long term study of the ice properties of the GrIS.

Rayleigh wave ellipticity measurements (the horizontal-to-vertical ratio of Rayleigh wave particle motions) are particularly sensitive to the subsurface structure beneath a seismic station. Using the polarisation properties of seismic noise, we extract Rayleigh wave ellipticity measurements from the Earth’s ambient noise for on-ice stations deployed in Greenland from 2012-- 2018. For wave periods sensitive to the ice sheet (T ≤ 3.5 s), we observe significant deviation between ellipticity measurements extracted from noise and synthetic fundamental mode calculations using a single ice column. Using a forward modelling approach we show: (1) a slow seismic shear-wave velocity at the near surface, (2) seismic attenuation, quantified as the quality factor Q, is sensitive to the temperature, water content and density of the ice and (3) the excitation of Rayleigh wave overtones plays a leading role in perturbing the ellipticity. Our results highlight how the inclusion of Q and overtone information can fill important gaps in our knowledge of ice sheet temperature, density and water content, which are important for predictions of the future evolution of the GrIS.

How to cite: Jones, G., Ferreira, A., Kulessa, B., Schimmel, M., Berbellini, A., and Morelli, A.: Characterising ice sheet properties using Rayleigh wave ellipticity, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12006, https://doi.org/10.5194/egusphere-egu22-12006, 2022.

11:32–11:38
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EGU22-7552
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ECS
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On-site presentation
Karina Hansen et al.

Ten-year records of ice surface elevation changes derived from three GNSS stations placed on the interior of the Greenland ice sheet are used to assess the ability of CryoSat-2 radar altimetry to capture surface elevation changes during 2010-2021. We use GNSS interferometric reflectometry (GNSS-IR) to derive time series of continuous daily surface elevations. The footprint of GNSS-IR is about 1000 m2 and the accuracy is ±2cm, making it an excellent tool to validate ice surface height from satellite altimetry. We compare GNSS-IR derived ice surface elevations with CryoSat-2 derived surface elevations and find Cryosat-2 performs best at the GNSS site furthest north (GLS3) with a maximum difference of 12cm. The other GNSS sites have a higher residual range because of poorer data availability and local surface variations. The number of Cryosat-2 data points are roughly doubled from GLS1 and GLS2 to GLS3. GLS3 Is located in a very flat area of the ice sheet only moving 55m during 2011-2020. In contrast GLS1 moved 292m in the same period, clearly indicating a steeper slope to the ice sheet at this location, which we have difficulty correcting for because digital elevation models are associated with high uncertainty on the interior of the ice sheet. The strength of this assessment method lies in the continuous daily time series of surface elevation change derived from GNSS, as they clearly capture extreme short-term changes, which otherwise might have been perceived as errors in the radar altimetry measurements.

How to cite: Hansen, K., Larson, K. M., Willis, M. J., Colgan, W., Helm, V., and Khan, S. A.: Assessment of ESA CryoSat-2 radar altimetry data using GNSSdata at three sites on the Greenland Ice Sheet, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7552, https://doi.org/10.5194/egusphere-egu22-7552, 2022.

11:38–11:44
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EGU22-9115
Reflections of ice penetrating radar from surface features
(withdrawn)
Veit Helm et al.
11:44–11:50
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EGU22-2706
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ECS
Development of ice slabs in the high percolation zone of the Greenland Ice Sheet
(withdrawn)
Nicolas Jullien et al.

Wed, 25 May, 13:20–14:50

Chairpersons: Christian Hauck, Franziska Koch, Emma C. Smith

13:20–13:26
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EGU22-5865
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ECS
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On-site presentation
Johanna Klahold et al.

Over the past decades, ground-penetrating radar (GPR) has become a fundamental tool in glaciological studies thanks to its tremendous capacity to provide high-resolution images in snow and ice. 3D acquisitions in particular can give detailed information on the internal structure, properties, and dynamics of glaciers. For imaging and highlighting important englacial and subglacial features such as meltwater tunnels and voids, an analysis of the spatial distribution of diffractions in the data holds great potential. However, the diffracted wavefield typically has low amplitude and is often masked by more prominent arrivals. Diffraction separation and imaging procedures have already become topics of significant interest in the field of exploration seismology, and may potentially open new possibilities for the analysis of glacier GPR data.

Here, we explore the potential of recent advances in diffraction imaging for the analysis of alpine glacier GPR data. To this end, we consider a 3D data set acquired on the Haut Glacier d’Arolla (Valais, Switzerland) using a 70-MHz single-antenna real-time-sampling GPR system. The approach we use coherently approximates the dominant reflected wavefield and subtracts it from the data. The remaining diffracted wavefield is then enhanced using local coherent stacking. We find that this methodology is highly effective at isolating diffractions in glacier GPR data and provides clean images of the diffracting structures. Current work includes investigation of the correlation between these structures and the englacial and subglacial hydrological network.

How to cite: Klahold, J., Schwarz, B., Bauer, A., and Irving, J.: Diffraction imaging of alpine glacier GPR data, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5865, https://doi.org/10.5194/egusphere-egu22-5865, 2022.

13:26–13:32
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EGU22-7725
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ECS
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Virtual presentation
Falk Oraschewski et al.

The internal stratigraphy of alpine glaciers entails information about its past dynamics and accumulation rates. It further can be used for intercalibrating the age-depth scales of ice cores. The internal ice stratigraphy is often imaged using radar, but similar to polar ice sheets the deeper stratigraphy is often difficult to resolve with classical pulsed radar systems. For polar ice sheets, the introduction of phase coherent radars has illuminated this former echo-free zone (EFZ) and now patterns of folded, buckled and disrupted ice stratigraphy are clearly visible. Unfortunately, the new airborne and ground-based radar systems applied in polar regions are typically too heavy to be deployed in an alpine environment.

Here, we transfer the lightweight autonomous phase-sensitive radio-echo sounder (ApRES) to an alpine glacier targeting its echo-free zone (Colle Gnifetti, Italy/Switzerland). The ApRES is a coherent frequency modulated continuous wave radar with an integration time of 1 s per trace which we deployed in combination with a GNSS used in real time kinematic (RTK) mode. The latter allows repositioning of the antennas with sub-wavelength accuracy (approximately 5 cm) required to exploit the coherent signal. Like this, the radio-stratigraphy of the former EFZ at this site could be imaged using a matched filtering SAR method. The resulting radargrams cover former ice core sites (e.g., Ice Memory and KCC) and can be used to harmonize conflicting age-depth scales. This dataset will be analysed further in conjunction with ice-fabric measurements from ice cores to reveal how the anisotropic ice rheology imprints on the flow field of glaciers.

How to cite: Oraschewski, F., Koch, I., Ershadi, M., Hawkins, J., and Drews, R.: Illuminating the deeper radio-stratigraphy of an alpine glacier using SAR processing , EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7725, https://doi.org/10.5194/egusphere-egu22-7725, 2022.

13:32–13:38
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EGU22-3073
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ECS
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Highlight
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On-site presentation
Bastien Ruols et al.

Thanks to the excellent propagation characteristics of radar waves in ice, ground-penetrating radar (GPR) has been one of the key geophysical methods used in the field of glaciology over the last 50 years. Alpine glacier GPR surveys are typically performed either directly on the glacier surface (e.g., on foot, skis, or with snowmobiles), or by helicopter several tens of meters above the surface. Helicopter-based surveys allow the coverage of large areas safely and efficiently, but this comes at the expense of reduced resolution of glacier internal structures, particularly in the context of 3D surveys. On the other hand, ice-based acquisitions offer high-resolution opportunities, but are very time-consuming, often risky, and can be physically exhausting to perform. Recent advances in the development of drone technologies open new data acquisition possibilities for glacier GPR data, combining the advantages of both ice and air-based methods.

We have developed a drone-based GPR system that allows for safe and efficient high-resolution 3D and 4D data acquisition on alpine glaciers. Our custom-built GPR instrument uses real-time sampling to record traces of length 2800 ns, which corresponds to a depth of over 200 m in glacier ice. Each trace is stacked over 5000 times and acquired using a sampling frequency of 320 MHz, the latter of which is just enough to avoid aliasing with our single lightweight 70-MHz-center-frequency antenna. Traces are recorded at a rate of 14 Hz, meaning that a drone speed of at least 4 m/s can be considered while maintaining a sufficiently high trace density for high-resolution studies. This is at least four times faster than a conventional survey on foot. The total weight of our GPR system plus single transmit/receive antenna is around 2 kg. The drone used in our work has a maximum payload capacity of about 6 kg and is equipped with a radar-based ground sensor which enables us to follow the glacier surface topography during the flights. An independent differential GPS allows us to locate each recorded GPR trace with decimeter precision.

We performed initial testing of the above-described system in August 2021 on the Otemma glacier and successfully acquired around 70-line kilometers of 3D GPR data, over an 8-day period, covering a large portion of the glacier. In September 2021, we undertook additional fieldwork on the Tsanfleuron and Sex-Rouge glaciers and recorded 30-line kilometers of 3D GPR data in less than 3 days. We could then determine and model with high-precision the ice-thickness distribution over the Tsanfleuron pass. These first field results show the concrete benefit of drone-based GPR glacier surveys and motivate further development towards 3D and 4D studies.

How to cite: Ruols, B., Baron, L., and Irving, J.: Drone-based GPR system for 4D glacier data acquisition, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3073, https://doi.org/10.5194/egusphere-egu22-3073, 2022.

13:38–13:44
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EGU22-1852
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ECS
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Virtual presentation
Aleksandr Borisik et al.

Glaciers on Svalbard have been shrinking in recent decades in response to current climate change. Most of them have decreased in size, area and surface elevation with stable negative or even accelerated changes in mass balance. Many of them are of the polythermal type, and as they shrink, their thermal regime might also change significantly depending on climate and local parameters, such as distribution of ice facies, firn thickness, and other factors affecting hydrology and glacier movement. In this study, we used data from repeated GPR surveys in 2010/12 and 2020/21 to identify likely changes in the thermal regime of the two polythermal glaciers Fridtjovbreen and Erdmanbreen in the western part of the Nordenskiöldland. These changes we have identified by comparison of changes in the depth of the internal reflection horizon (IRH) which corresponds to the cold-temperate transition surface (CTS) in polythermal glaciers.

Comparison of radio-echo sounding (RES) data obtained along the same transverse and longitudinal transects shows that in the last decade the most prominent CTS changes have occurred in the upper western basin of the Fridtjovbreen, where the mean total ice thickness decreased with rate −0.76 m a-1 (from 151 to 144 m in 9 years), meanwhile the thickness of the temperate ice core decreased with rate −2.52 m a-1 (from 115 to 92 m). As a result, with a general reduction in the thickness of the glacier, its upper cold layer increased from 36 to 52 m. These changes we attribute to the reduction of the firn area in this basin, which resulted in less thermal insulation and water retention and internal refreezing, and, therefore, in the fast cold front penetration into the glacier body with rates more than 3 times higher than the glacier thinning.

How to cite: Borisik, A., Novikov, A., Lavrentiev, I., and Glazovsky, A.: Changes in the internal structure of polythermal glaciers over the last decade: the case study of Fridtjofbreen and Erdmanbreen from 2010 to 2021, Svalbard, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1852, https://doi.org/10.5194/egusphere-egu22-1852, 2022.

13:44–13:50
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EGU22-4179
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ECS
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Virtual presentation
Wojciech Gajek et al.

Calving of tidewater glaciers is a key driver of glacier mass loss as well as a significant contribution towards sea level rise. However, this dynamic process is still challenging to quantify. In addition, there are very few direct measurements of calving activity in Svalbard at daily to sub-daily resolution due to the requirement of continuous human labour at the calving front for field studies. Seismic instruments in the vicinity of glaciers offer the potential to circumvent this issue since they record ground motion signals, including those generated by calving events, with an unprecedented sub-second resolution. Such data sets are not affected by site conditions like poor visibility or darkness and, in the case of permanent regional seismological stations, already offer long-term datasets. Despite this, a knowledge gap remains which prevents making a direct link between precise calving volumes and seismic records. This study presents our effort made towards obtaining an estimate of volumetric ice loss from integrating seismic records with 3D millimetre-wave radar measurements of a tidewater glacier calving front. In the summer of 2021, an 8-day long time series of integrated measurements was acquired at the calving front of Hansbreen, South Spitsbergen. It included remote sensing observations from a millimetre-wave radar (AVTIS2), Terrestrial Laser Scanner and time-lapse cameras correlated with a seismic dataset from two local arrays deployed at direct vicinity of calving front and a closeby regional permanent seismological station in Hornsund. Integrating these datasets brings an opportunity to correlate visual observations of calving including volumetric ice loss derived from radar scans with seismic signatures registered at nearby seismic arrays. We explore various parameters that characterize observed calving events and develop a model linking chosen parameters with ice loss using machine learning techniques. Local arrays were installed for a limited time and the calibrated parameters are expected to change spatially. Therefore, we further transfer our approach and integrate decade long records from nearby permanent seismological station. Limiting data to a single station record reduces both the accuracy of estimated ice volume and spatial resolution. However, it enables us to apply detection algorithm trained using observed calvings to decade long records and, consequently, to revisit a decade long history of Hansbreen's calving.

How to cite: Gajek, W., Harcourt, W., and Pearce, D.: Hansbreen’s calving-driven ice loss derived from seismic data supported by millimetre-wave radar scans and neural networks, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4179, https://doi.org/10.5194/egusphere-egu22-4179, 2022.

13:50–13:56
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EGU22-10565
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Virtual presentation
Coline Mollaret et al.

Geoelectrical methods are widely used for permafrost investigations by research groups, government agencies and industry. Electrical Resistivity Tomography (ERT) surveys are typically performed only once to detect the presence or absence of permafrost. Exchange of data and expertise among users is limited and usually occurs bilaterally. Neither complete information about the existence of geophysical surveys on permafrost nor the data itself is available on a global scale. Given the potential gain for identifying permafrost evidence and their spatio-temporal changes, there is a strong need for coordinated efforts regarding data, metadata, guidelines, and expertise exchange. Repetition of ERT surveys is rare, even though it could provide a quantitative spatio-temporal measure of permafrost evolution, helping to quantify the effects of climate change at local (where the ERT survey takes place) and global scales (due to the inventory).

Our International Permafrost Association (IPA) action group (2021-2023) has the main objective of bringing together the international community interested in geoelectrical measurements on permafrost and laying the foundations for an operational International Database of Geoelectrical Surveys on Permafrost (IDGSP). Our contribution presents a new international database of electrical resistivity datasets on permafrost. The core members of our action group represent more than 10 research groups, who have already contributed their own metadata (currently > 200 profiles covering 15 countries). These metadata will be fully publicly accessible in the near future whereas access to the resistivity data may be either public or restricted. Thanks to this open-access policy, we aim at increasing the level of transparency, encouraging further data providers and fostering survey repetitions by new users.

The database is set up on a virtual machine hosted by the University of Fribourg. The advanced open-source relational database system PostgreSQL is used to program the database. Homogenization and standardization of a large number of data and metadata are among the greatest challenges, yet are essential to a structured relational database. In this contribution, we present the structure of the database, statistics of the metadata uploaded, as well as first results of repetitions from legacy geoelectrical measurements on permafrost. Guidelines and strategies are developed to handle repetition challenges such as changing survey configuration, changing geometry or inaccurate/missing metadata. First steps toward transparent and reproducible automated filtering and inversion of a great number of datasets will also be presented. By archiving geoelectrical data on permafrost, the ambition of this project is the reanalysis of the full database and its climatic interpretation.

How to cite: Mollaret, C., Hilbich, C., Herring, T., Farzamian, M., Buckel, J., Dafflon, B., Draebing, D., Fossaert, H., Gugerli, R., Hauck, C., Kunz, J., Lewkowicz, A., Limbrock, J. K., Maierhofer, T., Magnin, F., Pellet, C., Pfaehler, S., Scandroglio, R., and Uhlemann, S. and the IDGSP IPA Action Group: Initiation of an international database of geoelectrical surveys on permafrost to promote data sharing, survey repetition and standardized data reprocessing , EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10565, https://doi.org/10.5194/egusphere-egu22-10565, 2022.

13:56–14:02
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EGU22-10159
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ECS
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On-site presentation
Mihai O. Cimpoiasu et al.

High Arctic regions are experiencing an accelerated rise in temperatures, about three times more than the global average. As a result, the glacier coverage over these landscapes is reducing, uncovering soils which start their development by sustaining emergent microbial communities. These new systems will have a significant impact on the global carbon budget, thus monitoring and understanding their evolution becomes a necessity.

Geoelectrical methods have emerged as a fast, cost-effective and minimally invasive way of imaging soil moisture dynamics in the shallow subsurface. BGS PRIME technology is designed to facilitate low-power remote geoelectrical tomography by using an array of sensor electrodes. We are using such technology to monitor the year-round variability of soil electrical resistivity in 4D on a glacier forefield in the vicinity of Ny-Alesund, Svalbard. Until now, such assessment of soil properties was confined to the summer period due to harsh Arctic winter conditions making site access very difficult.

Two PRIME systems were deployed during the summer of 2021 on Midtre Lovénbreen glacier forefield, which exhibits a soil chronosequence extending from the youngest soils near the glacier snout up to soils of approximately 120 years old. The two geophysical systems are monitoring electrical resistivity within the top 2m of soil of approximately 5 and 60 years of age respectively, recording soil moisture and freeze-thaw dynamics within the active layer above the permafrost.

We present early results, a timeseries of 3D soil electrical resistivity models, that captured several precipitation events during the summer and the progression of the freezing front when soil temperatures dropped below 0 °C in October 2021. These results reveal differences in the hydrodynamic activity between the 5- and 60-year-old sites determined by soil properties and their location on the glacier forefield. In addition, soil cores were sampled from the vicinity of the PRIME systems. These were subsequently subjected to laboratory tests to describe the changes in electrical resistivity as a function of moisture content and during successive freeze-thaw cycles. Furthermore, we are working towards an integrated analysis and a more comprehensive model of soil evolution at our sites by combining geoelectrical measurements with point measurements of environmental parameters and microbiological activity.

How to cite: Cimpoiasu, M. O., Harrison, H., Meldrum, P., Wilkinson, P., Chambers, J., Bradley, J., Sommers, P., Schmidt, S. K., Irons, T., Liljestrand, D., Oroza, C., and Kuras, O.: Year-round high-resolution geoelectrical monitoring to improve the understanding of deglaciated soil evolution in the High Arctic , EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10159, https://doi.org/10.5194/egusphere-egu22-10159, 2022.

14:02–14:08
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EGU22-6575
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ECS
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On-site presentation
Teddi Herring and Antoni Lewkowicz

Electrical resistivity tomography (ERT) is a geophysical method that produces an estimate of subsurface resistivity distribution, which can be used to infer the presence and extent of frozen ground. Repeated ERT surveys indicate how subsurface temperature and ground ice conditions are changing over time, which is particularly important for evaluating the changes and risks associated with climate change. However, there is no existing framework for sharing ERT data and datasets are rarely published, making it difficult to find and use historical data to assess subsurface changes. To facilitate data sharing, we are developing a Canadian database for ERT surveys of permafrost.

A key component of this project is the development of an automated ERT data processing workflow to prepare datasets. Establishing best practices for data processing ensures that ERT results are optimized and standardized, which is essential so that changes in subsurface conditions can be reasonably interpreted. We also present our web-based data visualization tool that allows for targeted searching of surveys and plotting of selected results. By storing ERT data in a standardized and accessible way, our goal is to facilitate interpretations of permafrost change on a range of spatial and temporal scales and guide future research in permafrost science.

How to cite: Herring, T. and Lewkowicz, A.: Creating a database of electrical resistivity tomography surveys of permafrost in Canada and establishing best practices for data processing and sharing, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6575, https://doi.org/10.5194/egusphere-egu22-6575, 2022.

14:08–14:14
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EGU22-3192
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Virtual presentation
Toshiro Tanimoto and Jiong Wang

We have developed a method to determine shear-modulus (rigidity) structure for the upper 20-50m of the Earth. The method is based on the analysis of co-located pressure and seismic instruments. We applied this method to about 200 (co-located) stations in Alaska and examined seasonal variation in shallow shear-modulus structure at each site; in this report we quantify this seasonal change by taking the ratio (R) of the highest shear-modulus to the lowest throughout a year and use it as a characteristic feature for each station.

R is smaller than 2 at many stations but there are some stations in and near the Arctic zone that have R larger than 10. Such a large seasonal change implies that there occurs massive melting of shallow permafrost and a significant development of the active layer every summer. As a side product, because of such a huge reduction in near-surface shear-modulus, horizontal amplitudes in seismic noise become 30 times larger in summer than amplitudes in winter.

These seasonal changes may not be surprising because thawing of ice is common every summer in the permafrost region. But regions with large R show a systematic geographic pattern on a large-scale map; large-R stations are typically found near the coast (ocean) and tend to decrease toward the interior of the continent (Alaska and NW Canada). Large R stations are found in the NW Territories in Canada, the North Slope region northern side of the Brooks Range, near the Seaward Peninsula (west), and the Yukon-Kuskokwim Delta (west). These locations suggest a strong influence by the nearby ocean on the climate at each station. Proximity to the ocean (coast) seems to be an important factor in evaluating periglacial hazards.

There are a few exceptions in the northernmost coastal stations as they show small R despite the fact that they are at the coast. But the ICEsat-2 (satellite) data show that sea ice seems to remain thick near the peninsula (near Barrow, Alaska) much longer than other coastal areas in this study; temperature is colder because of thicker sea ice and the amount of melting at these exception sites remains low. This would strengthen the hypothesis that near-coastal ocean has strong influence on the climate of continental interior.

How to cite: Tanimoto, T. and Wang, J.: Strong Ocean Influence on Seasonal Changes in Shallow Shear-Modulus Structure in Alaska, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3192, https://doi.org/10.5194/egusphere-egu22-3192, 2022.

14:14–14:20
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EGU22-8555
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ECS
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On-site presentation
Henrik Grob et al.

In the Canadian Arctic, permafrost and permafrost-associated gas hydrates formed extensively during the last 1 Ma. After the last glaciation, a marine transgression followed and former terrestrially exposed shelf areas became submerged. Subaerial mean annual temperatures of -20°C or even less changed to present submarine bottom water temperatures near -1°C. The relict submarine permafrost and gas hydrates present in the Beaufort Sea still react to this ongoing thermal change which results in their continued degradation. Thawing permafrost and destabilisation of permafrost-associated gas hydrates may release previously trapped greenhouse gases and can lead to even further gas hydrate dissociation. Moreover, thawing permafrost poses a geohazard in form of landslides and ground collapses. Yet, both the extent of the submarine permafrost and the permafrost-associated gas hydrates are still not well known. Here, we present three different approaches using marine 2D multichannel seismic data to improve the current knowledge of the distribution of offshore permafrost and gas hydrates occurrences in the southern Canadian Beaufort Sea. The acoustic properties of permafrost are determined by the content of ice and unfrozen pore fluids. Changing permafrost conditions affect the elasticity of the medium making seismic methods appropriate for permafrost detection. First, we identify direct and indirect seismic reflection indicators from permafrost and gas hydrates by the presence of cross-cutting, polarity-reversed, and upward-bend reflections as well as velocity pull-ups and shallow pronounced high-amplitude reflections. Second, using diving-wave tomography provides insights into the near-surface permafrost structure by imaging the velocity structure in greater detail than achievable by standard velocity analyses.  And third, diffractions separated from the reflect