A document by Ian R.J. Lee. Click on the document to view its contents.

The nucleation and triggering of basal microseisms, or icequakes, at the bottom of glaciers as the ice flows over it can grant us valuable insights about deformation processes that occur at the bed. The collaborative efforts of Penn State University and the British Antarctic Survey (BAS) during the 2018/2019 austral summer enabled the deployment of several seismic arrays over 3 months in the Rutford Ice Stream in West Antarctica for monitoring natural source seismicity. Using the earthquake detection and location software QuakeMigrate, we generated unique high-resolution icequake catalogs, particularly at Rutford’s grounding line. Our data showed an unprecedented number of detected events which we used to resolve key topographical features and characteristics at the bed like sticky spots, and how they related to the continuous ice loading-slipping process at the bed. To properly quantify relations between events, we performed rigorous testing via manual event inspection at each array to determine a trigger threshold that aims to balance event coverage with artefact minimization. To handle the massive amounts of incoming seismic data and subsequent located icequakes, we also created a systematic data processing pipeline, and used machine learning clustering algorithms to resolve inter- & intra-clusters spatial and temporal relations. We present our pre-processing methods on handling similarly large datasets and present findings from our seismic data in combination with other data sources, like GPR and tidal gauge data, that improves our understanding of ice flow dynamics in the region.

Basal microseisms in Antarctica, or icequakes, are valuable data sources that we can use to determine features and processes at the bed to improve our understanding of ice flow dynamics in the region. In the 2018/19 austral summer, we collaborated with the British Antarctic Survey (BAS) to deploy several seismic arrays of short period instruments over ~2 months in Rutford Ice Stream in West Antarctica to monitor natural source seismicity. During this recording period, we detected several swarms of repeating icequakes (~40 s interevent time) at our grounding line array that originate from a common basal source, which we hypothesize to be stick-slip motion over sticky spots/asperities. Smaller scale repeating icequakes, both in terms of amplitude and interevent times, also exist among the original larger repeating icequakes and are also hypothesized to originate from multiple smaller sticky spots that had less consistent loading and slipping. We built an auto-picker to detect these repeating icequakes over our recording period and located them using the automatic earthquake location Python package QuakeMigrate, and here we present our results as well as what they tell us about the basal topography. Further investigation of the interevent offsets between repeating signals of varying amplitudes and their frequency characteristics via FFT will provide more insights into the basal features, which we will corroborate with GPR basal topography data. Relations of the repeating icequakes to aseismic slip and tides will also be investigated. The findings at our grounding line array, where the repeating icequakes were first detected, can later support similar searches at the inland arrays. Antarctic ice streams remain a major source of uncertainty in projections of sea level rise, and our work seeks to constrain this uncertainty by improving our understanding of ice stream dynamics through basal conditions.

Using samples from the South Pole Ice Core (SPC14), we present new bubble number-density (BND) measurements and a modeled temperature history reconstruction for the South Pole site back through ~18.5 ka. Additionally, we show that 3D micro-CT sample imagery can accurately quantify BND, enabling more rapid and efficient future analyses. Using sampling and imaging techniques previously established for analyses of the WAIS Divide ice core (Spencer et al., 2006; Fegyveresi et al., 2016), we measured BND as well as other bubble characteristics from just below pore close-off depth starting at ~160 m, down to ~1200 m, at 20-meter intervals (53 total samples), with typical values ranging between 800 and 900 bubbles cm-3 over this interval. These values are higher than any previously recorded for ice-core BND, indicative of both colder average temperatures, and higher average accumulation rates at South Pole. Below ~1100 m, we noted significant bubble loss owing to the onset of clathrate-hydrate formation. Using micro-CT technology, we also tested the use of 3D imagery to accurately measure and evaluate BND as a supplement and future alternative to painstaking thin-section measurements. We imaged a secondary set of ice-core samples at 100-meter intervals starting at 200 m, and across the sample total depth range. Once corrected for cut- and micro-bubbles, our results show comparable values and thus similar trends to the thin-section data. For our temperature model, we determined an accumulation record using both measured annual layer thicknesses as well as estimated d15N-derived firn-column thicknesses estimates. Our temperature reconstruction was calculated using the model developed by Spencer et al. (2006), and using a South Pole site-specific bubble-to-grain ratio (G) of 1.6. the reconstruction reveals a warming across the glacial-interglacial transition of ~7°C, with a relatively stable trend through the Holocene (< 0.4°C warming). These results are in close agreement with those reported by other independent paleothermometers (i.e. isotope- and firn-derived reconstructions). Results of our temperature reconstruction also reveal that using 3D micro-CT imagery in place of traditional thin-section techniques produces comparable results, but with even greater accuracy, and lower measures of uncertainty.

The Antarctic Ice Sheet remains one of the greatest sources of uncertainty for improving predictions of sea level rise, and constraining this uncertainty has long been a difficult challenge within glaciology and climate science. Cryoseismology, paired with the meteoric rise of data science applications within the geosciences, has emerged as a promising field well suited to answering these challenges as the improvement of sampling technology and access have resulted in a proliferation of Antarctic seismic data. Ice flow dynamics in Antarctica are significantly influenced by features and processes at the bed, and basal microseismicity from tremors as ice moves across the bed can yield valuable information for resolving the glacier subsurface. We deployed high-frequency (up to 1000 Hz) geophone arrays at Rutford Ice Stream over the 2018-2019 austral summer to monitor the natural source seismicity from the base of the ice and generate an event catalog. To efficiently process the enormous volumes of cryoseismic data to locate events, we used the Python package QuakeMigrate which utilizes a parallelized waveform stacking algorithm to detect coherent seismic phase arrivals across our network. Over three months of data, we located over 1,700,000 seismic events (majority which were microseismic) within a 4 km x 4 km square grid around our 13-station, ~3.25 km2 area array. The detection and location of icequakes at this resolution provides a unique opportunity to investigate the temporal, location, and size relations between events, and we present the findings from our data mined event catalog and document the QuakeMigrate parameter tuning to optimize event location. The significant amounts of data collected of the region over the past decades mean that the literature and documentation of conditions at Rutford is more complete relative to most of Antarctica, and our work aims to contribute towards a comprehensive survey of an Antarctic region.

Rapid retreat of the Larsen A and B ice shelves has provided important clues about the ice shelf destabilization processes. The Larsen C Ice Shelf, the largest remaining ice shelf on the Antarctic Peninsula, may also be vulnerable to future collapse in a warming climate. Here, we utilize multi-source satellite images collected over 1963–2020 to derive multidecadal time series of ice front, flow velocities, and critical rift features over Larsen C, with the aim of understanding the controls on its retreat. We complement these observations with modeling experiments using the Ice-sheet and Sea-level System Model to examine how front geometry conditions and mechanical weakening due to rifts affect ice shelf dynamics. Over the past six decades, Larsen C lost over 20% of its area, dominated by rift-induced tabular iceberg calving. The Bawden Ice Rise and Gipps Ice Rise are critical areas for rift formation, through their impact on the longitudinal deviatoric stress field. Mechanical weakening around Gipps Ice Rise is found to be a primary control on localized flow acceleration, leading to the propagation of two rifts that caused a major calving event in 2017. Capturing the time-varying effects of rifts on ice rigidity in ice shelf models is essential for making realistic predictions of ice shelf flow dynamics and instability. In the context of the Larsen A and Larsen B collapses, we infer a chronology of destabilization processes for embayment-confined ice shelves, which provides a useful framework for understanding the historical and future destabilization of Antarctic ice shelves.