{"dp_type": "Project", "free_text": "Basal Elevation"}
[{"awards": "2209726 Lindzey, Laura", "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": "QIceRadar Antarctic Index of Radar Depth Sounding Data", "datasets": [{"dataset_uid": "200413", "doi": " 10.5281/zenodo.12123013", "keywords": null, "people": null, "repository": "Zenodo", "science_program": null, "title": "QIceRadar Antarctic Index of Radar Depth Sounding Data", "url": "https://zenodo.org/records/12123013"}], "date_created": "Wed, 19 Jun 2024 00:00:00 GMT", "description": "Ice penetrating radar is one of the primary tools that researchers use to study ice sheets and glaciers. With radar, it is possible to see a cross-section of the ice, revealing internal layers and the shape of the rocks under the ice. Among other things, this is important for calculating how much potential sea level change is locked up in the polar ice sheets, and how stable the ice sheets are likely to be in a warming world. This type of data is logistically challenging and expensive to collect. Historically, individual research groups have obtained funding to collect these data sets, and then the data largely stayed within that institution. There has been a recent push to make more and more data openly available, enabling the same datasets to be used by multiple research groups. However, it is still difficult to figure out what data is available because there is no centralized index. Additionally, each group releases data in a different format, which creates an additional hurdle to its use. This project addresses both of those challenges to data reuse by providing a unified tool for discovering where ice penetrating radar data already exists, then allowing the researcher to download and visualize the data. It is integrated into open-source mapping software that many in the research community already use, and makes it possible for non-experts to explore these datasets. This is particularly valuable for early-career researchers and for enabling interdisciplinary work. The US alone has spent many tens of millions of dollars on direct grants to enable the acquisition and analysis of polar ice penetrating radar data, and even more on the associated infrastructure and support costs. Unfortunately, much of these data is not publicly released, and even the data that has been released is not easily accessible. There is significant technical work involved in figuring out how to locate, download and view the data. This project is developing a tool that will both lower the barrier to entry for using this data and improve the workflows of existing users. Quantarctica and QGreenland have rapidly become indispensable tools for the polar research community, making diverse data sets readily available to researchers. However, ice penetrating radar is a major category of data that is not currently supported \u2013 it is possible to see the locations of existing survey lines, and the ice thickness maps that have been interpreted from their data, but it is not readily possible to see the radargrams themselves in context with all of the other information. This capability is important because there is far more visual information contained in a radargram than simply its interpreted basal elevation or ice thickness. This project is developing software that will enable researchers to to view radargram images and interpreted surface and basal horizons in context with the existing map-view datasets in Quantarctica and QGreenland. A data layer shows the locations of all known ice penetrating radar surveys, color-coded based on availability. This layer enables data discovery and browsing. The plugin itself interacts with the data layer, first to download selected data, then to visualize the radargrams along with a cursor that moves simultaneously along the radargram and along the map view, making it straightforward to determine the precise geolocation of radar features. This award reflects NSF\u0027s statutory mission and has been deemed worthy of support through evaluation using the Foundation\u0027s intellectual merit and broader impacts review criteria.", "east": 180.0, "geometry": "POINT(0 -89.999)", "instruments": null, "is_usap_dc": true, "keywords": "AIRCRAFT; GLACIERS/ICE SHEETS; Antarctica", "locations": "Antarctica", "north": -60.0, "nsf_funding_programs": "Polar Cyberinfrastructure", "paleo_time": null, "persons": "Lindzey, Laura", "platforms": "AIR-BASED PLATFORMS \u003e PROPELLER \u003e AIRCRAFT", "repo": "Zenodo", "repositories": "Zenodo", "science_programs": null, "south": -90.0, "title": "Elements: Making Ice Penetrating Radar More Accessible: A tool for finding, downloading and visualizing georeferenced radargrams within the QGIS ecosystem", "uid": "p0010464", "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 | |||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
|
Elements: Making Ice Penetrating Radar More Accessible: A tool for finding, downloading and visualizing georeferenced radargrams within the QGIS ecosystem
|
2209726 |
2024-06-19 | Lindzey, Laura |
|
Ice penetrating radar is one of the primary tools that researchers use to study ice sheets and glaciers. With radar, it is possible to see a cross-section of the ice, revealing internal layers and the shape of the rocks under the ice. Among other things, this is important for calculating how much potential sea level change is locked up in the polar ice sheets, and how stable the ice sheets are likely to be in a warming world. This type of data is logistically challenging and expensive to collect. Historically, individual research groups have obtained funding to collect these data sets, and then the data largely stayed within that institution. There has been a recent push to make more and more data openly available, enabling the same datasets to be used by multiple research groups. However, it is still difficult to figure out what data is available because there is no centralized index. Additionally, each group releases data in a different format, which creates an additional hurdle to its use. This project addresses both of those challenges to data reuse by providing a unified tool for discovering where ice penetrating radar data already exists, then allowing the researcher to download and visualize the data. It is integrated into open-source mapping software that many in the research community already use, and makes it possible for non-experts to explore these datasets. This is particularly valuable for early-career researchers and for enabling interdisciplinary work. The US alone has spent many tens of millions of dollars on direct grants to enable the acquisition and analysis of polar ice penetrating radar data, and even more on the associated infrastructure and support costs. Unfortunately, much of these data is not publicly released, and even the data that has been released is not easily accessible. There is significant technical work involved in figuring out how to locate, download and view the data. This project is developing a tool that will both lower the barrier to entry for using this data and improve the workflows of existing users. Quantarctica and QGreenland have rapidly become indispensable tools for the polar research community, making diverse data sets readily available to researchers. However, ice penetrating radar is a major category of data that is not currently supported – it is possible to see the locations of existing survey lines, and the ice thickness maps that have been interpreted from their data, but it is not readily possible to see the radargrams themselves in context with all of the other information. This capability is important because there is far more visual information contained in a radargram than simply its interpreted basal elevation or ice thickness. This project is developing software that will enable researchers to to view radargram images and interpreted surface and basal horizons in context with the existing map-view datasets in Quantarctica and QGreenland. A data layer shows the locations of all known ice penetrating radar surveys, color-coded based on availability. This layer enables data discovery and browsing. The plugin itself interacts with the data layer, first to download selected data, then to visualize the radargrams along with a cursor that moves simultaneously along the radargram and along the map view, making it straightforward to determine the precise geolocation of radar features. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. | 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 |
