High‐Frequency (>2 Hz) Ambient Seismic Noise on High‐Melt Glaciers: Green's Function Estimation and Source Characterization

Abstract

Using ambient noise to characterize subsurface structures has revolutionized solid earth seismology. In glacial applications, this technique could provide valuable information about ice thickness and bed properties, which to date are deduced from laborious and/or expensive active source geophysics or deep drilling. Despite challenging conditions such as minimal scattering and changing sources, we show that stacks of cross‐correlation functions of several hours of ambient seismic noise can converge towards Green's functions under favorable conditions. These contain the sought‐after information about subsurface seismic velocities and ice thickness. Applying this technique to two Alpine glaciers in Switzerland, we calculate signal‐to‐noise ratios of noise correlation functions. Faster Green's functions convergence during elevated ambient noise levels suggests that increased surface melt promotes spatially homogeneous excitation of noise sources. With the help of Green's functions amplitude asymmetry as well as standard beamforming, we locate dominant noise sources. In combination with spectrograms, glacier surface velocities from GPS and proglacial water discharge measurements, we find glacier noise in the range from 2 to 8 Hz to be a combination of tremor induced by flowing water, icequakes, and anthropogenic sources. We finally calculate dispersion curves from the cross‐correlation functions to arrive at an estimate of the ice thickness. In combination with H/V spectral ratios, the method shown here allows sampling the depth and the properties of the glacier bed by deploying only two seismometers for several hours. Ambient noise correlations could therefore be a valuable ingredient for studies of glacier and ice sheet beds.

Seasonal and Diurnal Dynamics of Subglacial Channels: Observations Beneath an Alpine Glacier

“…4 and 5). A similar frequency-signature of the subglacial channel-flow-induced seismic noise as been observed by Bartholomaus et al (2015), Preiswerk and Walter (2018) and Lindner et al (2019) in glacial environments. This frequency range is also comparable to those observed for terrestrial rivers (Burtin et al, 2008;Schmandt et al, 2013).…”

Glaciohydraulic seismic tremors on an Alpine glacier

“…We then calculate the bedrock topography by subtracting the ice thickness from the digital elevation model. Subsequently, we calculate the hydraulic potential for f = 1.0 (water pressure equals the ice overburden pressure), since we expect high water pressures, especially during the lake drainage initiation (Roberts, 2005). This is confirmed by continuous GPS measurements in the vicinity of A0, A2, and A3, which show vertical lifting during the first ≈ 8-36 h of the lake drainage (Fig.…”

“…To investigate likely subglacial water-flow paths, we calculate the upstream area for each grid cell, i.e., the (grid cell) area that is upstream and connected to the grid cell of consideration. We follow the approach of Flowers and Clarke (1999) and calculate the upstream area distribution using the Quinn algorithm (Quinn et al, 1991), which transfers the area to all downstream cells among the eight direct neigh-bor cells weighted by the relative gradients. We perform depression filling of the hydraulic potential surfaces and subsequent calculation of the upstream area using the RichDEM toolbox (Barnes, 2016).…”

“…Such a configuration is often encountered in the early melt season (Iken and Bindschadler, 1986;Werder et al, 2013). In addition, drainage events of glacier-dammed lakes can inject large volumes of water on short timescales, exceeding the capacity of the subglacial conduits and causing a pressurization of the system (Roberts, 2005). By modulating the effective pressure at the glacier bed, glacier hydraulics play a key role in ice flow dynamics (Iken and Bindschadler, 1986).…”

On the Green's function emergence from interferometry of seismic wave fields generated in high-melt glaciers: implications for passive imaging and monitoring

“…Such topics are currently investigated with active seismic experiments or through the spatiotemporal evolution of passive seismicity and associated source mechanisms (e.g. Walter et al, 2008;Bartholomaus et al, 2015;Preiswerk et al, 2016;Podolskiy et al, 2017;Lipovsky et al, 2019). Passive seismic monitoring of glaciers could lead to the detection and understanding of processes related to climate conditions, glacier hydraulics, and ice flow dynamics, which today are labor-intensive to investigate with active geophysical measurements.…”