{"dp_type": "Project", "free_text": "Filchner Ice Shelf"}
[{"awards": "1643455 Enderlin, Ellyn; 1933764 Enderlin, Ellyn", "bounds_geometry": "POLYGON((-180 -60,-144 -60,-108 -60,-72 -60,-36 -60,0 -60,36 -60,72 -60,108 -60,144 -60,180 -60,180 -63,180 -66,180 -69,180 -72,180 -75,180 -78,180 -81,180 -84,180 -87,180 -90,144 -90,108 -90,72 -90,36 -90,0 -90,-36 -90,-72 -90,-108 -90,-144 -90,-180 -90,-180 -87,-180 -84,-180 -81,-180 -78,-180 -75,-180 -72,-180 -69,-180 -66,-180 -63,-180 -60))", "dataset_titles": "Crane Glacier centerline observations and modeling results ; Remotely-sensed iceberg geometries and meltwater fluxes", "datasets": [{"dataset_uid": "601679", "doi": "10.15784/601679", "keywords": "Antarctica; Elevation; Glaciology; Iceberg; Meltwater; Submarine Melt", "people": "Dickson, Adam; Oliver, Caitlin; Enderlin, Ellyn; Aberle, Rainey; Dryak, Mariama; Miller, Emily", "repository": "USAP-DC", "science_program": null, "title": "Remotely-sensed iceberg geometries and meltwater fluxes", "url": "https://www.usap-dc.org/view/dataset/601679"}, {"dataset_uid": "601617", "doi": "10.15784/601617", "keywords": "Antarctica; Antarctic Peninsula; Crane Glacier; Glacier Dynamics; Glacier Mass Discharge; Glaciers/ice Sheet; Glaciers/Ice Sheet; Glaciology; Modeling; Model Output", "people": "Marshall, Hans-Peter; Kopera, Michal; Meehan, Tate; Aberle, Rainey; Enderlin, Ellyn", "repository": "USAP-DC", "science_program": null, "title": "Crane Glacier centerline observations and modeling results ", "url": "https://www.usap-dc.org/view/dataset/601617"}], "date_created": "Mon, 28 Jun 2021 00:00:00 GMT", "description": "The project uses repeat, very high-resolution (~0.5 m pixel width and length) satellite images acquired by the WorldView satellites, to estimate rates of iceberg melting in key coastal regions around Antarctica. The satellite images are used to construct maps of iceberg surface elevation change over time, which are converted to estimates of area-averaged submarine melt rates. Where ocean temperature observations are available, the melt rates are compared to these data to determine if variations in ocean temperature can explain observed iceberg melt variability. The iceberg melt rates are also compared to glacier frontal ablation rates (flow towards the terminus minus changes in terminus position over time) and integrated into a numerical ice flow model in order to assess the importance of submarine melting on recent changes in terminus position, ice flow, and dynamic mass loss. Overall, the analysis will yield insights into the effects of changes in ocean forcing on the submarine melting of Antarctic ice shelves and icebergs. The project does not require field work in Antarctica.", "east": 180.0, "geometry": "POINT(0 -89.999)", "instruments": null, "is_usap_dc": true, "keywords": "Amery Ice Shelf; FIELD SURVEYS; Totten Glacier; GLACIER MASS BALANCE/ICE SHEET MASS BALANCE; USAP-DC; Antarctic Peninsula; ICEBERGS; Mertz Glacier; OCEAN TEMPERATURE; USA/NSF; Amd/Us; Amundsen Sea; Ronne Ice Shelf; Filchner Ice Shelf; AMD", "locations": "Antarctic Peninsula; Totten Glacier; Ronne Ice Shelf; Filchner Ice Shelf; Amery Ice Shelf; Mertz Glacier; Amundsen Sea", "north": -60.0, "nsf_funding_programs": "Antarctic Glaciology; Antarctic Glaciology", "paleo_time": null, "persons": "Enderlin, Ellyn", "platforms": "LAND-BASED PLATFORMS \u003e FIELD SITES \u003e FIELD SURVEYS", "repo": "USAP-DC", "repositories": "USAP-DC", "science_programs": null, "south": -90.0, "title": "Antarctic Submarine Melt Variability from Remote Sensing of Icebergs", "uid": "p0010210", "west": -180.0}, {"awards": "0229292 Cressie, Noel", "bounds_geometry": null, "dataset_titles": null, "datasets": null, "date_created": "Wed, 28 Feb 2007 00:00:00 GMT", "description": "Ice streams are believed to play a major role in determining the response of their parent ice sheet to climate change, and in determining global sea level by serving as regulators on the fresh water stored in the ice sheets. Ice streams are characterized by rapid, laterally confined flow which makes them uniquely identifiable within the body of the more slowly and more homogeneously flowing ice sheet. But while these characteristics enable the identification of ice streams, the processes which control ice-stream motion and evolution, and differences among ice streams in the polar regions, are only partially understood. Understanding the relative importance of lateral and basal drags, as well as the role of gradients in longitudinal stress, is essential for developing models for future evolution of the polar ice\u003cbr/\u003esheets. In this project, physical statistical models will be used to explore the processes that control ice-stream flow, and to compare these processes between seemingly different ice-stream systems. In particular, Whillans Ice Stream draining into the Ross Ice Shelf, will be compared with Recovery and RAMP glaciers draining into the Ronne-Filchner Ice Shelf, and the Northeast Ice Stream in Greenland. Geophysical models lie at the core of the approach, but are embellished by modeling various components of variability statistically. One important component comes from the uncertainty in observations on basal elevation, surface elevation, and surface velocity. In this project new observational data collected using remote-sensing techniques will be used. The various components, some of which are spatial, are combined hierarchically using Bayesian statistical methodology. All these components will be combined mathematically into a physical statistical model that yields the posterior distribution for basal, longitudinal, and lateral stress fields, and velocity fields, conditional on the data. Inference based on this distribution will be carried out via Markov chain Monte Carlo techniques, to obtain estimates of these unknown fields along with uncertainty measures associated with them.", "east": null, "geometry": null, "instruments": null, "is_usap_dc": false, "keywords": "Surface Elevation; Stress Field; Basal Elevation; DHC-6", "locations": null, "north": null, "nsf_funding_programs": "Antarctic Glaciology", "paleo_time": null, "persons": "Cressie, Noel; Jezek, Kenneth; Berliner, L.", "platforms": "AIR-BASED PLATFORMS \u003e PROPELLER \u003e DHC-6", "repositories": null, "science_programs": null, "south": null, "title": "Dynamics of Ice Streams: A Physical Statistical Approach", "uid": "p0000711", "west": null}]
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Project Title/Abstract/Map | NSF Award(s) | Date Created | PIs / Scientists | Dataset Links and Repositories | Abstract | Bounds Geometry | Geometry | Selected | Visible | |||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Antarctic Submarine Melt Variability from Remote Sensing of Icebergs
|
1643455 1933764 |
2021-06-28 | Enderlin, Ellyn |
|
The project uses repeat, very high-resolution (~0.5 m pixel width and length) satellite images acquired by the WorldView satellites, to estimate rates of iceberg melting in key coastal regions around Antarctica. The satellite images are used to construct maps of iceberg surface elevation change over time, which are converted to estimates of area-averaged submarine melt rates. Where ocean temperature observations are available, the melt rates are compared to these data to determine if variations in ocean temperature can explain observed iceberg melt variability. The iceberg melt rates are also compared to glacier frontal ablation rates (flow towards the terminus minus changes in terminus position over time) and integrated into a numerical ice flow model in order to assess the importance of submarine melting on recent changes in terminus position, ice flow, and dynamic mass loss. Overall, the analysis will yield insights into the effects of changes in ocean forcing on the submarine melting of Antarctic ice shelves and icebergs. The project does not require field work in Antarctica. | POLYGON((-180 -60,-144 -60,-108 -60,-72 -60,-36 -60,0 -60,36 -60,72 -60,108 -60,144 -60,180 -60,180 -63,180 -66,180 -69,180 -72,180 -75,180 -78,180 -81,180 -84,180 -87,180 -90,144 -90,108 -90,72 -90,36 -90,0 -90,-36 -90,-72 -90,-108 -90,-144 -90,-180 -90,-180 -87,-180 -84,-180 -81,-180 -78,-180 -75,-180 -72,-180 -69,-180 -66,-180 -63,-180 -60)) | POINT(0 -89.999) | false | false | |||||
Dynamics of Ice Streams: A Physical Statistical Approach
|
0229292 |
2007-02-28 | Cressie, Noel; Jezek, Kenneth; Berliner, L. | No dataset link provided | Ice streams are believed to play a major role in determining the response of their parent ice sheet to climate change, and in determining global sea level by serving as regulators on the fresh water stored in the ice sheets. Ice streams are characterized by rapid, laterally confined flow which makes them uniquely identifiable within the body of the more slowly and more homogeneously flowing ice sheet. But while these characteristics enable the identification of ice streams, the processes which control ice-stream motion and evolution, and differences among ice streams in the polar regions, are only partially understood. Understanding the relative importance of lateral and basal drags, as well as the role of gradients in longitudinal stress, is essential for developing models for future evolution of the polar ice<br/>sheets. In this project, physical statistical models will be used to explore the processes that control ice-stream flow, and to compare these processes between seemingly different ice-stream systems. In particular, Whillans Ice Stream draining into the Ross Ice Shelf, will be compared with Recovery and RAMP glaciers draining into the Ronne-Filchner Ice Shelf, and the Northeast Ice Stream in Greenland. Geophysical models lie at the core of the approach, but are embellished by modeling various components of variability statistically. One important component comes from the uncertainty in observations on basal elevation, surface elevation, and surface velocity. In this project new observational data collected using remote-sensing techniques will be used. The various components, some of which are spatial, are combined hierarchically using Bayesian statistical methodology. All these components will be combined mathematically into a physical statistical model that yields the posterior distribution for basal, longitudinal, and lateral stress fields, and velocity fields, conditional on the data. Inference based on this distribution will be carried out via Markov chain Monte Carlo techniques, to obtain estimates of these unknown fields along with uncertainty measures associated with them. | None | None | false | false |