Shallow Ice‐Sheet Composite Structure Revealed by Seismic Imaging Near the West Antarctic Ice Sheet (WAIS) Divide Camp

Abstract

Small‐scale polar ice‐sheet composite structures can influence coarse‐grained climate models. For example, surface melting can hydro‐fracture the ice and may eventually lubricate the base. The drainage process will change the petrophysical properties of the subsurface and is predictable from high‐resolution seismic imaging. Ray‐based imaging methods, though limited by the approximations made, have mapped seismic velocities in 1D, but have yet to offer definitive information about the lateral heterogeneity. Here we use the wave‐equation‐based seismic imaging method to estimate shear‐wave velocities and to image an englacial reflector in 2D. We use 7‐day ambient‐noise data recorded by a linear array near the West Antarctic Ice Sheet (WAIS) Divide drilling site to perform the study. We obtain 2D vertical and horizontal shear‐wave velocity models and observe a lateral variation of the radial anisotropy along the acquisition line. The inverted velocity model is further used to estimate the thicknesses of firn‐air and firn layers. We also observe evident SH reflections and calculate the reflector image using robust zero‐offset imaging and a more precise reverse time migration imaging method. The imaged reflector is at about 1,700 m depth and is dipping to the southwest. We anticipate that a porosity change at that depth may cause this englacial seismic discontinuity near WAIS Divide. Our results demonstrate the feasibility of estimating the petrophysical properties of polar ice using seismic methods. We anticipate our work to be further used for understanding ice dynamics and thermodynamics, such as the stability of ice shelves, the retreat of the Antarctic ice sheet, and restoring the paleo‐sedimentary environment.

High‐Resolution Characterization of the Firn Layer Near the West Antarctic Ice Sheet Divide Camp With Active and Passive Seismic Data

“…However, challenges persist in accurately characterizing firn properties (Maupin, 2017;Tanimoto et al, 2013). For instance, Zhang et al (2022) constructed a shear-wave velocity (V S ) model in the upper 300 m through ambient noise tomography using data from a seismic array close to the WAIS Divide camp (Figure 1a), acquired as part of the Thwaites Interdisciplinary Margin Evolution (TIME) project (hereafter termed the "TIME array"). However, the model of Zhang et al (2022) offers little constraint of the uppermost firn layer given limited data quality and sensitivity to shallow structures, and the predicted Rayleigh wave phase velocities (V ph ) consistently exceed observations at frequencies >25 Hz.…”

“…However, the model of Zhang et al. (2022) offers little constraint of the uppermost firn layer given limited data quality and sensitivity to shallow structures, and the predicted Rayleigh wave phase velocities (V ph ) consistently exceed observations at frequencies >25 Hz. This also reduces the value of the method for further modeling studies.…”

Firn Seismic Anisotropy in the North East Greenland Ice Stream from Ambient Noise Surface Waves

“…Schlegel et al, 2019;Hollmann et al, 2021;Pearce et al, 2023;Picotti et al, 2015), distributed acoustic sensing methods (Zhou et al, 2022;Fichtner et al, 2023), or from ambient noise, (e.g. Chaput et al, 2022;Lévêque et al, 2010;Diez et al, 2016;Zhang et al, 2022). The use of seismic methods can give a unique insight into the firn anisotropy that is otherwise difficult to obtain.…”

“…Diez et al (2016) retrieved Rayleigh and Love waves from noise and inverted them for shear velocity (V sh and V sv ) profiles at the Ross Ice Shelf. Zhang et al (2022) uses seven days of ambient-noise data to obtain 2-D vertical and horizontal shear-wave velocity models. Azimuthal anisotropy within firn has been explored using DAS by Zhou et al (2022).…”

“…With the advancement of seismic nodes (a compact all-in-one 3-channel, wireless seismometer), small dense seismic arrays are being deployed in polar regions (e.g. Gimbert et al, 2021;Chaput et al, 2022;Zhang et al, 2022), giving rise to the possibility of using ambient noise-based tomography to study shallower structures and anisotropy. The most notable advantages of this method are that ambient seismic noise exists in all places, (with varying spatial and temporal variations), and that the method utilises a passive acquisition with relatively easy deployment.…”