{"dp_type": "Dataset", "free_text": "Ice-Sheet Stability"}
[{"awards": "1914698 Hansen, Samantha", "bounds_geometry": ["POLYGON((90 -65,99 -65,108 -65,117 -65,126 -65,135 -65,144 -65,153 -65,162 -65,171 -65,180 -65,180 -67.5,180 -70,180 -72.5,180 -75,180 -77.5,180 -80,180 -82.5,180 -85,180 -87.5,180 -90,171 -90,162 -90,153 -90,144 -90,135 -90,126 -90,117 -90,108 -90,99 -90,90 -90,90 -87.5,90 -85,90 -82.5,90 -80,90 -77.5,90 -75,90 -72.5,90 -70,90 -67.5,90 -65))"], "date_created": "Wed, 24 Jan 2024 00:00:00 GMT", "description": "Recent investigations in polar environments have examined solid-Earth-ice-sheet feedbacks and have emphasized that glacial isostatic adjustment, tectonic, and geothermal forcings exert first-order control on the physical conditions at and below the ice-bed interface and must be taken into account when evaluating ice-sheet evolution. However, the solid-Earth structure beneath much of Antarctica is still poorly constrained given the sparse distribution of seismic stations across the continent and the generally low seismicity rate. One region of particular interest is the Wilkes Subglacial Basin (WSB) in East Antarctica. During the mid-Pliocene warm period, the WSB may have contributed 3-4 m to the estimated 20 m rise in sea-level, indicating that this region could also play an important role in future warming scenarios. However, the WSB may have experienced notable bedrock uplift since the Pliocene; therefore, past geologic inferences of instability may not serve as a simple analogue for the future.\r\n\r\nUsing records of ambient seismic noise recorded by both temporary and long-term seismic networks, along with a full-waveform tomographic inversion technique, we have developed improved images of the lithospheric structure beneath East Antarctica, including the WSB. Empirical Green\u2019s Functions with periods between 40 and 340 s have been extracted using a frequency-time normalization technique, and a finite-difference approach with a spherical grid has been employed to numerically model synthetic seismograms. Associated sensitivity kernels have also been constructed using a scattering integral method. Our results suggest the WSB is underlain by slow seismic velocities, with faster seismic structure beneath the adjacent Transantarctic Mountains and the Belgica Subglacial Highlands. This may indicate that the WSB is associated with a region of thinner lithosphere, possibly associated with prior continental rifting. The seismic heterogeneity highlighted in our model could have significant implications for understanding the geodynamic origin of WSB topography and its influence on ice-sheet behavior.\r\n\r\nThe model file and associated plotting scripts are provided.", "east": 180.0, "geometry": ["POINT(135 -77.5)"], "keywords": "Ambient Noise; Antarctica; East Antarctica; Geoscientificinformation; Seismic Tomography; Seismology", "locations": "Antarctica; East Antarctica", "north": -65.0, "nsf_funding_programs": "Antarctic Earth Sciences", "persons": "Hansen, Samantha; Emry, Erica", "project_titles": "Collaborative Research: Resolving earth structure influence on ice-sheet stability in the Wilkes\r\nSubglacial Basin (RESISSt)", "projects": [{"proj_uid": "p0010204", "repository": "USAP-DC", "title": "Collaborative Research: Resolving earth structure influence on ice-sheet stability in the Wilkes\r\nSubglacial Basin (RESISSt)"}], "repo": "USAP-DC", "repositories": "USAP-DC", "science_programs": null, "south": -90.0, "title": "Full Waveform Ambient Noise Tomography for East Antarctica", "uid": "601763", "west": 90.0}, {"awards": "1914698 Hansen, Samantha", "bounds_geometry": ["POLYGON((148 -71.5,150.4 -71.5,152.8 -71.5,155.2 -71.5,157.6 -71.5,160 -71.5,162.4 -71.5,164.8 -71.5,167.2 -71.5,169.6 -71.5,172 -71.5,172 -72.15,172 -72.8,172 -73.45,172 -74.1,172 -74.75,172 -75.4,172 -76.05,172 -76.7,172 -77.35,172 -78,169.6 -78,167.2 -78,164.8 -78,162.4 -78,160 -78,157.6 -78,155.2 -78,152.8 -78,150.4 -78,148 -78,148 -77.35,148 -76.7,148 -76.05,148 -75.4,148 -74.75,148 -74.1,148 -73.45,148 -72.8,148 -72.15,148 -71.5))"], "date_created": "Wed, 24 Jan 2024 00:00:00 GMT", "description": "As seismic data availability increases, the necessity for automated processing techniques has become increasingly evident. Expanded geophysical datasets collected over the past several decades across Antarctica provide excellent resources to evaluate different event detection approaches. We have used the traditional Short-Term Average/Long-Term Average (STA/LTA) algorithm to catalogue seismic data recorded by 19 stations in East Antarctica between 2012 and 2015. However, the complexities of the East Antarctic dataset, including low magnitude events and phenomena such as icequakes, warrant more advanced automated detection techniques. Therefore, we have also applied template matching as well as several deep learning algorithms, including Generalized Phase Detection (GPD), PhaseNet, BasicPhaseAE, and EQTransformer (EQT), to identify seismic phases within our dataset. Our goal was not only to increase the volume of detectable seismic events but also to gain insights into the effectiveness of these different automated approaches. Our assessment evaluated the completeness of the newly generated catalogs, the precision of identified event locations, and the quality of the picks. The final events corresponding to each of our three catalogs (based on STA/LTA, template matching, and machine learning, respectively) are listed in the provided files.", "east": 172.0, "geometry": ["POINT(160 -74.75)"], "keywords": "Antarctica; Geoscientificinformation; Machine Learning; Seismic Event Detection; Seismology; Seismometer", "locations": "Antarctica", "north": -71.5, "nsf_funding_programs": "Antarctic Earth Sciences", "persons": "Hansen, Samantha; Ho, Long; Walter, Jacob", "project_titles": "Collaborative Research: Resolving earth structure influence on ice-sheet stability in the Wilkes\r\nSubglacial Basin (RESISSt)", "projects": [{"proj_uid": "p0010204", "repository": "USAP-DC", "title": "Collaborative Research: Resolving earth structure influence on ice-sheet stability in the Wilkes\r\nSubglacial Basin (RESISSt)"}], "repo": "USAP-DC", "repositories": "USAP-DC", "science_programs": null, "south": -78.0, "title": "East Antarctic Seismicity from different Automated Event Detection Algorithms", "uid": "601762", "west": 148.0}]
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| Dataset Title/Abstract/Map | NSF Award(s) | Date Created | PIs / Scientists | Project Links | Abstract | Bounds Geometry | Geometry | Selected | Visible |
|---|---|---|---|---|---|---|---|---|---|
|
Full Waveform Ambient Noise Tomography for East Antarctica
|
1914698 |
2024-01-24 | Hansen, Samantha; Emry, Erica |
Collaborative Research: Resolving earth structure influence on ice-sheet stability in the Wilkes
Subglacial Basin (RESISSt) |
Recent investigations in polar environments have examined solid-Earth-ice-sheet feedbacks and have emphasized that glacial isostatic adjustment, tectonic, and geothermal forcings exert first-order control on the physical conditions at and below the ice-bed interface and must be taken into account when evaluating ice-sheet evolution. However, the solid-Earth structure beneath much of Antarctica is still poorly constrained given the sparse distribution of seismic stations across the continent and the generally low seismicity rate. One region of particular interest is the Wilkes Subglacial Basin (WSB) in East Antarctica. During the mid-Pliocene warm period, the WSB may have contributed 3-4 m to the estimated 20 m rise in sea-level, indicating that this region could also play an important role in future warming scenarios. However, the WSB may have experienced notable bedrock uplift since the Pliocene; therefore, past geologic inferences of instability may not serve as a simple analogue for the future. Using records of ambient seismic noise recorded by both temporary and long-term seismic networks, along with a full-waveform tomographic inversion technique, we have developed improved images of the lithospheric structure beneath East Antarctica, including the WSB. Empirical Green’s Functions with periods between 40 and 340 s have been extracted using a frequency-time normalization technique, and a finite-difference approach with a spherical grid has been employed to numerically model synthetic seismograms. Associated sensitivity kernels have also been constructed using a scattering integral method. Our results suggest the WSB is underlain by slow seismic velocities, with faster seismic structure beneath the adjacent Transantarctic Mountains and the Belgica Subglacial Highlands. This may indicate that the WSB is associated with a region of thinner lithosphere, possibly associated with prior continental rifting. The seismic heterogeneity highlighted in our model could have significant implications for understanding the geodynamic origin of WSB topography and its influence on ice-sheet behavior. The model file and associated plotting scripts are provided. | ["POLYGON((90 -65,99 -65,108 -65,117 -65,126 -65,135 -65,144 -65,153 -65,162 -65,171 -65,180 -65,180 -67.5,180 -70,180 -72.5,180 -75,180 -77.5,180 -80,180 -82.5,180 -85,180 -87.5,180 -90,171 -90,162 -90,153 -90,144 -90,135 -90,126 -90,117 -90,108 -90,99 -90,90 -90,90 -87.5,90 -85,90 -82.5,90 -80,90 -77.5,90 -75,90 -72.5,90 -70,90 -67.5,90 -65))"] | ["POINT(135 -77.5)"] | false | false |
|
East Antarctic Seismicity from different Automated Event Detection Algorithms
|
1914698 |
2024-01-24 | Hansen, Samantha; Ho, Long; Walter, Jacob |
Collaborative Research: Resolving earth structure influence on ice-sheet stability in the Wilkes
Subglacial Basin (RESISSt) |
As seismic data availability increases, the necessity for automated processing techniques has become increasingly evident. Expanded geophysical datasets collected over the past several decades across Antarctica provide excellent resources to evaluate different event detection approaches. We have used the traditional Short-Term Average/Long-Term Average (STA/LTA) algorithm to catalogue seismic data recorded by 19 stations in East Antarctica between 2012 and 2015. However, the complexities of the East Antarctic dataset, including low magnitude events and phenomena such as icequakes, warrant more advanced automated detection techniques. Therefore, we have also applied template matching as well as several deep learning algorithms, including Generalized Phase Detection (GPD), PhaseNet, BasicPhaseAE, and EQTransformer (EQT), to identify seismic phases within our dataset. Our goal was not only to increase the volume of detectable seismic events but also to gain insights into the effectiveness of these different automated approaches. Our assessment evaluated the completeness of the newly generated catalogs, the precision of identified event locations, and the quality of the picks. The final events corresponding to each of our three catalogs (based on STA/LTA, template matching, and machine learning, respectively) are listed in the provided files. | ["POLYGON((148 -71.5,150.4 -71.5,152.8 -71.5,155.2 -71.5,157.6 -71.5,160 -71.5,162.4 -71.5,164.8 -71.5,167.2 -71.5,169.6 -71.5,172 -71.5,172 -72.15,172 -72.8,172 -73.45,172 -74.1,172 -74.75,172 -75.4,172 -76.05,172 -76.7,172 -77.35,172 -78,169.6 -78,167.2 -78,164.8 -78,162.4 -78,160 -78,157.6 -78,155.2 -78,152.8 -78,150.4 -78,148 -78,148 -77.35,148 -76.7,148 -76.05,148 -75.4,148 -74.75,148 -74.1,148 -73.45,148 -72.8,148 -72.15,148 -71.5))"] | ["POINT(160 -74.75)"] | false | false |
