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Given the high number and diversity of events in a typical cryoseismic dataset, in particular those recorded on ice sheet margins, it is desirable to use a semi-automated method of grouping similar events for reconnaissance and ongoing analysis. We present a workflow for employing semi-unsupervised cluster analysis to inform investigations of the processes occurring in glaciers and ice sheets. In this demonstration study, we make use of a seismic event catalogue previously compiled for the Whillans Ice Stream, for the 2010–2011 austral summer outlined in Part 1,. We address the challenges of seismic event analysis for a complex wave field by clustering similar seismic events into groups using characteristic temporal, spectral, and polarization attributes of seismic time series with the k -means++ algorithm. This provides the basis for a reconnaissance analysis of a seismic wave field that contains local events (from the ice stream) set in an ambient wave field that itself contains a diversity of signals (mostly from the Ross Ice Shelf). As one result, we find that two clusters include stick-slip events that diverge in terms of length and initiation locality (i.e., central sticky spot and/or the grounding line). We also identify a swarm of high-frequency signals on 16–17 January 2011 that are potentially associated with a surface melt event from the Ross Ice Shelf. Used together with the event detection presented in Part 1, the semi-automated workflow could readily be generalized to other locations and, as a possible benchmark procedure, could enable the monitoring of remote glaciers over time and comparisons between locations. [ABSTRACT FROM AUTHOR]

Seismic Rayleigh wave ellipticity measurements are the horizontal-to-vertical ratio of the Rayleigh wave particle motion, and are sensitive to the subsurface structure beneath a seismic station. H/V ratios measured from the ambient vibrations of the Earth are being increasingly used in glaciological applications to determine glacier and ice sheet thickness, seismic velocities and firn properties. Using the newly developed degree-of-polarisation (DOP-E) method which exploits the polarisation properties of seismic noise, we identify and extract Rayleigh waves from seismic stations in Greenland, and relate them to sea ice processes and the geology of the upper crust. Finally, we provide some suggestions for future applications of DOP-E method to gain greater insight into seasonal and long-term variability of sea ice formation and breakup as well as the monitoring of ice sheet thickness, subglacial environment and firn layers in the poles. [ABSTRACT FROM AUTHOR]

Given the high number and diversity of events in a typical cryoseismic dataset, in particular those recorded on ice sheet margins, it is desirable to use a semi-automated method of grouping similar events for reconnaissance and ongoing analysis. We present a workflow for employing semi-unsupervised cluster analysis to inform investigations of the processes occurring in glaciers and ice sheets. In this demonstration study, we make use of a seismic event catalogue previously compiled for the Whillans Ice Stream, for the 2010–2011 austral summer (outlined in companion paper, Latto et al., 2023). We address the challenges of seismic event analysis for a complex wavefield by clustering similar seismic events into groups using characteristic temporal, spectral, and polarization attributes of seismic time series with the k-means++ algorithm. This provides the basis for a reconnaissance analysis of a seismic wavefield that contains local events (from the ice stream) set in an ambient wavefield that itself contains a diversity of signals (mostly from the Ross Ice Shelf). As one result, we find that two clusters include stick-slip events that diverge in terms of length and initiation locality (i.e. Central Sticky Spot and/or the grounding line). We also identify a swarm of high frequency signals on January 16–17, 2011 that are potentially associated with a surface melt event from the Ross Ice Shelf. Used together with the event detection presented in the companion paper, the semi-automated workflow could readily generalize to other locations, and as a possible benchmark procedure, could enable the monitoring of remote glaciers over time and comparisons between locations. [ABSTRACT FROM AUTHOR]

Over the past 70 years, many different components of the cryosphere have been imaged with a variety of radar systems using increasingly sophisticated processing techniques. These systems use various pulse lengths, signal frequencies and, in some cases, modulated signals. The increasing diversity of radar systems has created the potential for confusion due to the use of non-consistent terminology. Here we provide an overview of state-of-the-science radar technologies and suggest a simplified and unified terminology for use by the cryosphere community. We recommend a terminology that is target independent but specifies the characteristics of the signal. Following this recommendation, commercial impulse systems that penetrate the subsurface should be referred to as ground-penetrating radar (GPR), and pulse radars as radio-echo sounding (RES). Continuous-wave (CW) radar systems should be referred to as ground-penetrating CW radars. We further suggest any additional characterisation of the system be expressed using descriptors that specify the platform it is mounted on (e.g. airborne) or the frequency range (e.g. HF (high frequency)) or modulation (e.g. FM (frequency modulated)). [ABSTRACT FROM AUTHOR]

To understand snow structure and snowmelt timing, information about flows of liquid water within the snowpack is essential. Models can make predictions using explicit representations of physical processes, or through parameterization, but it is difficult to verify simulations. In situ observations generally measure bulk quantities. Where internal snowpack measurements are made, they tend to be destructive and unsuitable for continuous monitoring. Here, we present a novel method for in situ monitoring of water flow in seasonal snow using the electrical self-potential (SP) geophysical method. A prototype geophysical array was installed at Col de Porte (France) in October 2018. Snow hydrological and meteorological observations were also collected. Results for two periods of hydrological interest during winter 2018–19 (a marked period of diurnal melting and refreezing, and a rain-on-snow event) show that the electrical SP method is sensitive to internal water flow. Water flow was detected by SP signals before it was measured in conventional snowmelt lysimeters at the base of the snowpack. This initial feasibility study shows the utility of the SP method as a non-destructive snow sensor. Future development should include combining SP measurements with a high-resolution snow physics model to improve prediction of melt timing. [ABSTRACT FROM AUTHOR]