Stick‐Slip Tremor Beneath an Alpine Glacier

Abstract

Sliding of glacial ice over its base is typically the dominant flow mechanism of glaciers and ice sheets. The term "sliding" is often used in a loose sense to include the deformation of "soft" till beds and the differential motion between basal ice and underlying bedrock. The amount of sliding controls fast (Clarke, 1987) and slow (Maier et al., 2019) ice flow regimes. Sliding variations are powerful enough to halt, or even reverse, ice stream flow (Conway et al., 2002) or rupture ice tongues, leading to massive ice avalanches (Faillettaz et al., 2015; Kääb et al., 2018). Nevertheless, sliding mechanisms remain elusive, leading to uncertain predictions of ice sheet motion and stability, and ultimately sea level rise (

Matched Field Processing accounting for complex Earth structure: method and review

“…5a, SCEDC, 2013). The good fit here confirms what other authors have found before: standard MFP can already perform quite well in seismological studies (Gal et al, 2018;Umlauft & Korn, 2019;Umlauft et al, 2021). When we replace s(ω, x j , x s ) with numerical Green's functions (our approach) for an explosive source mechanism, we at first find a decrease in location accuracy (Fig.…”

“…This requires prior knowledge of v and the assumption that v = const is a good approximation of the medium. In seismology, this approach has been successfully demonstrated on local scale (e.g., Corciulo et al, 2012;Umlauft & Korn, 2019;Umlauft et al, 2021),…”

“…This demonstrates one of the potential use cases for MFP with numerical Green's functions: Searching for the best-fitting moment tensor may help constrain the source mechanism of unknown weak sources. A related strategy has been employed by Umlauft et al (2021). The authors flipped the sign of waveforms, based on visual inspection and expert judgement, before applying MFP.…”

“…Synthetic wave fields are computed for these travel times and matched against the recorded wave field. In the seismological context, MFP has been applied succesfully on local (Corciulo et al, 2012;Umlauft & Korn, 2019;Umlauft et al, 2021) and regional scale (Gal et al, 2018). Recent developments in MFP include the development of different beamformers (e.g., Zhu et al, 2020), improved estimation of travel times (Gal et al, 2018), or estimating synthetic wave fields empirically (Gibbons et al, 2017).…”

Estimation of Resolution and Covariance of Ambient Seismic Source Distributions: Full Waveform Inversion and Matched Field Processing

“…One often estimates the spatial ambient seismic source distributions (strength and location) when studying ambient seismic sources. One can image source locations using traditional imaging methods without expensive computation [e.g., matched‐field processing (MFP), Baggeroer et al., 1988; Bucker, 1976], for example, to investigate glacier tremors (e.g., Umlauft et al., 2021) or the hydrothermal system at Old Faithful Geyser (e.g., Cros et al., 2011). In using MFP, one crosscorrelates ambient seismic recordings to extract coherent signals and then apply backprojection to the crosscorrelations to image the source locations (e.g., Cros et al., 2011).…”