Firn Seismic Anisotropy in the North East Greenland Ice Stream from Ambient Noise Surface Waves
We analyse ambient noise seismic data from 23 three-component seismic nodes to study firn velocity structure and seismic anisotropy near the EastGRIP camp along the Northeast Greenland Ice Stream (NEGIS). Using 9-component correlation tensors, we derive dispersion curves of Rayleigh and Love wave gr...
Main Authors: | , , , , , , , |
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Format: | Text |
Language: | English |
Published: |
2023
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Subjects: | |
Online Access: | https://doi.org/10.5194/egusphere-2023-2192 https://egusphere.copernicus.org/preprints/2023/egusphere-2023-2192/ |
Summary: | We analyse ambient noise seismic data from 23 three-component seismic nodes to study firn velocity structure and seismic anisotropy near the EastGRIP camp along the Northeast Greenland Ice Stream (NEGIS). Using 9-component correlation tensors, we derive dispersion curves of Rayleigh and Love wave group velocities from 3 Hz to 40 Hz. These velocity distributions exhibit anisotropy along and across the flow. To assess these variations, we invert dispersion curves for shear wave velocities (V sh and V sv ) in the top 150 m of NEGIS using a Markov Chain Monte Carlo approach. The reconstructed1-D shear velocity model reveals radial anisotropy in the firn, with V sh 12 %–15 % greater than V sv , peaking at the critical density (550 kg m –3 ). We combine density data from firn cores drilled in 2016 and 2018 to create a new density parameterisation for NEGIS, serving as a reference for our results. We link seismic anisotropy in the NEGIS to effective and intrinsic causes. Seasonal densification, wind crusts, and melt layers induce effective anisotropy, leading to faster V sh waves. Changes in firn recrystalisation cause intrinsic anisotropy, altering the V sv to V sh ratio. We observe a shallower firn-ice transition across flow (≈ 50 m) compared to along flow (≈ 60 m), suggesting increased firn compaction due to the predominant wind direction and increased deformation towards the shear margin. We demonstrate that short-duration (nine-day minimum), passive, seismic deployments, and noise-based analysis can determine seismic anisotropy in firn, and reveal 2-D firn structure and variability. |
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