Subglacial lakes require a thawed bed either now or in the past; thus, their presence and stability have implications for current and past basal conditions, ice dynamics, and climate. Here, we present the most extensive geophysical exploration to date of a subglacial lake near the geographic South Pole, including radar‐imaged stratigraphy, surface velocities, and englacial vertical velocities. We use a 1.5‐dimensional temperature model, optimized with our geophysical data set and nearby temperature measurements, to estimate past basal‐melt rates. The ice geometry, reflected bed‐echo power, surface and vertical velocities, and temperature model indicate that the ice‐bed interface is regionally thawed, contradicting prior studies. Together with an earlier active‐source seismic study, which showed a 32‐m deep lake underlain by 150 m of sediment, our results suggest that the lake has been thermodynamically stable through at least the last 120,000 years and possibly much longer, making it a promising prospective site for sediment coring.
An Unsupervised Machine‐Learning Approach to Understanding Seismicity at an Alpine Glacier
It is critical to understand the dynamic conditions of Earth's cryosphere, yet the subglacial and englacial environments that control many aspects of ice behavior are inherently difficult to observe. The study of seismicity in glaciers and ice sheets has provided valuable insights about the cryosphere for decades, more recently aided by tools from machine learning. Here, we present an unsupervised machine‐learning approach to discovering and interpreting cryoseismic patterns using 5 weeks of seismic data recorded at Gornergletscher, Switzerland. Our algorithm utilizes non‐negative matrix factorization and hidden Markov modeling to reduce spectrograms into characteristic, low‐dimensional “fingerprints,” which we reduce further using principal component analysis, then cluster using k‐means clustering. We investigate the timing, locations, and statistical properties of the clusters in relation to temperature, GPS and lake‐level measurements, and find that signals associated with lake flooding tend to occupy one cluster, whereas signals associated with afternoon and evening melt‐water flow reside in others. We suggest that the one cluster contains signals that include the true initiation of the flood's englacial and subglacial drainage components. This work demonstrates an unsupervised machine‐learning approach to exploring both continuous and event‐based glacial seismic data.
more » « less- NSF-PAR ID:
- 10388057
- Publisher / Repository:
- DOI PREFIX: 10.1029
- Date Published:
- Journal Name:
- Journal of Geophysical Research: Earth Surface
- Volume:
- 127
- Issue:
- 12
- ISSN:
- 2169-9003
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
more » « less
Abstract -
Antarctica is almost completely covered by the world’s largest ice sheet, and its hidden geologic structure partially controls the behavior of the ice layer. Recent advances in geophysical and remote sensing tools have allowed us to observe various transient phenomena, such as tectonic earthquakes, glacial bed slip events, and iceberg calving signals, all of which can be used to investigate solid Earth – cryosphere interactions. We analyzed seismic data collected by the TAMNNET temporary deployment as well as other stations in East Antarctica to identify and locate local icequakes, earthquakes, and other seismic events that occurred between 2012-2015. We employ two event detection approaches. The first is based on phase match filtering and waveform cross-correlation, which uses known events as templates to search through continuous data and to identify similar seismic signals. The second uses EQtransformer, a deep-learning-based event signal detector and phase picker. Event detections identified with both approaches will be compared to assess the effectiveness of these methods in East Antarctica. We also plan to use the combined constraints from our initial approaches to train a new machine-learning model and to assess its performance. Ultimately, our results will be used to evaluate automated event detection approaches for polar environments and to address fundamental questions related to tectonic-cryospheric interactions.more » « less
-
null (Ed.)Abstract The continuously growing amount of seismic data collected worldwide is outpacing our abilities for analysis, since to date, such datasets have been analyzed in a human-expert-intensive, supervised fashion. Moreover, analyses that are conducted can be strongly biased by the standard models employed by seismologists. In response to both of these challenges, we develop a new unsupervised machine learning framework for detecting and clustering seismic signals in continuous seismic records. Our approach combines a deep scattering network and a Gaussian mixture model to cluster seismic signal segments and detect novel structures. To illustrate the power of the framework, we analyze seismic data acquired during the June 2017 Nuugaatsiaq, Greenland landslide. We demonstrate the blind detection and recovery of the repeating precursory seismicity that was recorded before the main landslide rupture, which suggests that our approach could lead to more informative forecasting of the seismic activity in seismogenic areas.more » « less
-
Abstract The earliest airborne geophysical campaigns over Antarctica and Greenland in the 1960s and 1970s collected ice penetrating radar data on 35 mm optical film. Early subglacial topographic and englacial stratigraphic analyses of these data were foundational to the field of radioglaciology. Recent efforts to digitize and release these data have resulted in geometric and ice-thickness analysis that constrain subsurface change over multiple decades but stop short of radiometric interpretation. The primary challenge for radiometric analysis is the poorly-characterized compression applied to Z-scope records and the sparse sampling of A-scope records. Here, we demonstrate the information richness and radiometric interpretability of Z-scope records. Z-scope pixels have uncalibrated fast-time, slow-time, and intensity scales. We develop approaches for mapping each of these scales to physical units (microseconds, seconds, and signal to noise ratio). We then demonstrate the application of this calibration and analysis approach to a flight in the interior of East Antarctica with subglacial lakes and to a reflight of an East Antarctic ice shelf that was observed by both archival and modern radar. These results demonstrate the potential use of Z-scope signals to extend the baseline of radiometric observations of the subsurface by decades.more » « less
-
East Antarctica is covered by thick sheets of ice and is underlain by stable cratonic lithosphere, extensive mountain ranges, and subglacial basins. The sparse seismic coverage in this region makes it difficult to assess the crustal and mantle structure, which are important to understanding the tectonic evolution of the continent as well as the behavior of the overlying ice sheets. Present tomographic models lack resolution and are often inconsistent with one another; therefore, delineating sub-surface characteristics associated with old rift systems or structures that would allow us to assess the origins of the Wilkes and Aurora subglacial basins, for instance, becomes challenging. To overcome these limitations, we are using a full-waveform tomography method to model the crustal and upper mantle structure in East Antarctica. We have used a frequency-time normalization approach to extract empirical Green’s functions (EGFs) from ambient seismic noise, between periods of 15-340 seconds. The ray path coverage of the EGFs is dense throughout East Antarctica, indicating that our study will provide new, high resolution imaging of this area. Synthetic waveforms are simulated through a three-dimensional heterogeneous Earth model using a finite-difference wave propagation method with a grid spacing of 0.025º (~ 2.25 km), which accurately reproduce Rayleigh waves at 15+ seconds. Following this, phase delays are measured between the synthetics and the data, sensitivity kernels are constructed using a scattering integral approach, and we invert using a sparse, least-squares method. The resulting shear-wave velocity model will be used to assess crustal and upper mantle features, ultimately aimed at resolving whether old rift systems exist within East Antarctica in relation to prominent subglacial basins. Preliminary results will be shared.more » « less
