{"dp_type": "Dataset", "free_text": "Downscaling"}
[{"awards": "2136938 Tedesco, Marco", "bounds_geometry": ["POLYGON((-40 67.55,-39.611 67.55,-39.222 67.55,-38.833 67.55,-38.444 67.55,-38.055 67.55,-37.666 67.55,-37.277 67.55,-36.888 67.55,-36.499 67.55,-36.11 67.55,-36.11 67.28999999999999,-36.11 67.03,-36.11 66.77,-36.11 66.51,-36.11 66.25,-36.11 65.99,-36.11 65.73,-36.11 65.47,-36.11 65.21000000000001,-36.11 64.95,-36.499 64.95,-36.888 64.95,-37.277 64.95,-37.666 64.95,-38.055 64.95,-38.444 64.95,-38.833 64.95,-39.222 64.95,-39.611 64.95,-40 64.95,-40 65.21000000000001,-40 65.47,-40 65.73,-40 65.99,-40 66.25,-40 66.51,-40 66.77,-40 67.03,-40 67.28999999999999,-40 67.55))"], "date_created": "Mon, 07 Oct 2024 00:00:00 GMT", "description": "This dataset contains high-resolution satellite-derived snow/ice surface melt-related data on a common 100 m equal area grid (Albers equal area projection; EPSG 9822) over Helheim Glacier and surrounding areas in Greenland. The data is used as part of a machine learning framework that aims to fill data gaps in computed meltwater fraction on the 100 m grid using a range of methods, results of which will be published separately.\r\n\u003cbr/\u003e\u003cbr/\u003e\r\n\u003cbr/\u003e\u003cbr/\u003eThe data include fraction of a grid cell covered by meltwater derived from Sentinel-1 synthetic aperture radar (SAR) backscatter, satellite-derived passive microwave (PMW) brightness temperatures, snowpack liquid water content within the first meter of snow and atmospheric and radiative variables from the Mod\u00e9le Atmosph\u00e9rique R\u00e8gional (MAR) regional climate model, spectral reflectance in four wavelength bands from the Moderate Resolution Imaging Spectroradiometer (MODIS), a static digital elevation model (DEM), and an ice sheet mask. \r\n\u003cbr/\u003e\u003cbr/\u003eA similar dataset has also been produced for Larsen C ice shelf and is also available through the US Antarctic Program Data Center. \r\n\u003cbr/\u003e\u003cbr/\u003e\r\n\u003cbr/\u003e\u003cbr/\u003e\r\n\u003cbr/\u003e\u003cbr/\u003e", "east": -36.11, "geometry": ["POINT(-38.055 66.25)"], "keywords": "Antarctica; Climate Modeling; Cryosphere; Downscaling; Glaciers/ice Sheet; Glaciers/Ice Sheet; Glaciology; Greenland; Ice Sheet; Machine Learning; MAR; Remote Sensing; Sea Level Rise; Snow/ice; Snow/Ice; Surface Melt", "locations": "Greenland; Antarctica; Greenland", "north": 67.55, "nsf_funding_programs": "Polar Cyberinfrastructure", "persons": "Alexander, Patrick; Antwerpen, Raphael; Cervone, Guido; Fettweis, Xavier; L\u00fctjens, Bj\u00f6rn; Tedesco, Marco", "project_titles": "Collaborative Research: EAGER: Generation of high resolution surface melting maps over Antarctica using regional climate models, remote sensing and machine learning", "projects": [{"proj_uid": "p0010277", "repository": "USAP-DC", "title": "Collaborative Research: EAGER: Generation of high resolution surface melting maps over Antarctica using regional climate models, remote sensing and machine learning"}], "repo": "USAP-DC", "repositories": "USAP-DC", "science_programs": null, "south": 64.95, "title": "Surface melt-related multi-source remote-sensing and climate model data over Helheim Glacier, Greenland for segmentation and machine learning applications", "uid": "601841", "west": -40.0}, {"awards": "2136938 Tedesco, Marco", "bounds_geometry": ["POLYGON((-68.5 -65.25,-67.35 -65.25,-66.2 -65.25,-65.05 -65.25,-63.9 -65.25,-62.75 -65.25,-61.6 -65.25,-60.45 -65.25,-59.3 -65.25,-58.15 -65.25,-57 -65.25,-57 -65.652,-57 -66.054,-57 -66.456,-57 -66.858,-57 -67.25999999999999,-57 -67.66199999999999,-57 -68.064,-57 -68.466,-57 -68.868,-57 -69.27,-58.15 -69.27,-59.3 -69.27,-60.45 -69.27,-61.6 -69.27,-62.75 -69.27,-63.9 -69.27,-65.05 -69.27,-66.2 -69.27,-67.35 -69.27,-68.5 -69.27,-68.5 -68.868,-68.5 -68.466,-68.5 -68.064,-68.5 -67.66199999999999,-68.5 -67.25999999999999,-68.5 -66.858,-68.5 -66.456,-68.5 -66.054,-68.5 -65.652,-68.5 -65.25))"], "date_created": "Mon, 07 Oct 2024 00:00:00 GMT", "description": "This dataset contains high-resolution satellite-derived snow/ice surface melt-related data on a common 100 m equal area grid (Lambert azimuthal equal area projection; EPSG 9820) over Larsen C Ice Shelf and surrounding areas in Antarctica. The data is prepared to be used as part of a machine learning framework that aims to fill data gaps in computed meltwater fraction on the 100 m grid using a range of methods, results of which will be published separately.\r\n\u003cbr/\u003e\u003cbr/\u003e\u003cbr/\u003eThe data include fraction of a grid cell covered by meltwater derived from Sentinel-1 synthetic aperture radar (SAR) backscatter, satellite-derived passive microwave (PMW) brightness temperatures, snowpack liquid water content within the first meter of snow and atmospheric and radiative variables from the Mod\u00e9le Atmosph\u00e9rique R\u00e8gional (MAR) regional climate model, a static digital elevation model (DEM), and an ice sheet mask. \r\n\u003cbr/\u003e\u003cbr/\u003e\u003cbr/\u003eA similar dataset has been produced for Helheim Glacier, Greenland and is also available through the US Antarctic Program Data Center.", "east": -57.0, "geometry": ["POINT(-62.75 -67.25999999999999)"], "keywords": "Antarctica; Climate Modeling; Cryosphere; Downscaling; Glaciers/ice Sheet; Glaciers/Ice Sheet; Glaciology; Ice Shelf; Larsen C Ice Shelf; Machine Learning; MAR; Remote Sensing; Sea Level Rise; Snow/ice; Snow/Ice; Surface Melt", "locations": "Antarctica; Larsen C Ice Shelf", "north": -65.25, "nsf_funding_programs": "Polar Cyberinfrastructure", "persons": "Alexander, Patrick; Antwerpen, Raphael; Cervone, Guido; Fettweis, Xavier; L\u00fctjens, Bj\u00f6rn; Tedesco, Marco", "project_titles": "Collaborative Research: EAGER: Generation of high resolution surface melting maps over Antarctica using regional climate models, remote sensing and machine learning", "projects": [{"proj_uid": "p0010277", "repository": "USAP-DC", "title": "Collaborative Research: EAGER: Generation of high resolution surface melting maps over Antarctica using regional climate models, remote sensing and machine learning"}], "repo": "USAP-DC", "repositories": "USAP-DC", "science_programs": null, "south": -69.27, "title": "Surface melt-related multi-source remote-sensing and climate model data over Larsen C Ice Shelf, Antarctica for segmentation and machine learning applications", "uid": "601842", "west": -68.5}, {"awards": "1141973 Tedesco, Marco", "bounds_geometry": ["POLYGON((-94.7374 -56.9464,-89.23679 -56.9464,-83.73618 -56.9464,-78.23557 -56.9464,-72.73496 -56.9464,-67.23435 -56.9464,-61.73374 -56.9464,-56.23313 -56.9464,-50.73252 -56.9464,-45.23191 -56.9464,-39.7313 -56.9464,-39.7313 -59.19838,-39.7313 -61.45036,-39.7313 -63.70234,-39.7313 -65.95432,-39.7313 -68.2063,-39.7313 -70.45828,-39.7313 -72.71026,-39.7313 -74.96224,-39.7313 -77.21422,-39.7313 -79.4662,-45.23191 -79.4662,-50.73252 -79.4662,-56.23313 -79.4662,-61.73374 -79.4662,-67.23435 -79.4662,-72.73496 -79.4662,-78.23557 -79.4662,-83.73618 -79.4662,-89.23679 -79.4662,-94.7374 -79.4662,-94.7374 -77.21422,-94.7374 -74.96224,-94.7374 -72.71026,-94.7374 -70.45828,-94.7374 -68.2063,-94.7374 -65.95432,-94.7374 -63.70234,-94.7374 -61.45036,-94.7374 -59.19838,-94.7374 -56.9464))"], "date_created": "Fri, 01 Jan 2016 00:00:00 GMT", "description": "This award supports a project to generate first-time validated enhanced spatial resolution (5-10 km) maps of surface melting over the Antarctic Peninsula for the period 1958 - to date from the outputs of a regional climate model and different downscaling techniques. These maps will be assessed and validated through new high spatial resolution (2.25 km) surface melting maps obtained from the QuikSCAT satellite for the period 1999 - 2009. The intellectual merit of this work is that it would be the first time that the outputs of a regional climate model would be used to study surface melting over Antarctica at such high spatial resolution and the first time that such results are validated by means of an observational tool that has such a large spatial coverage and high spatial resolution. The results generated in this study would also provide a first-time opportunity to study the melt distribution over the Peninsula and its correlation with climate drivers, such as the Southern Annual Mode (SAM) and the El Nino-Southern Oscillation (ENSO) at these unprecedented spatial scales. The enhanced resolution melting maps will also offer a unique opportunity to study melting trends and patterns over specific regions of the Peninsula, such as the Wilkins and the Larsen A and B ice shelves and evaluate whether the extreme melting observed during the recent collapses was unprecedented over the + 50 years. The broader impacts of the project are that it will integrate research and education by fully supporting one female undergrad student, a PhD student and partially supporting a PostDoc. The work will be done at a minority-serving institution and the PhD student who worked on the development of the high-resolution melting data set from QuikSCAT will become the PostDoc who will work on this project. Teaching and learning will be supported by incorporating research results into graduate and undergrad level courses and will be disseminated over the web and through appropriate channels. Results from this project will also benefit the society at large as they will improve our understanding of the links between atmospheric patterns and surface melting and they will contribute to improving estimates of sea level rise from the Antarctica continent.", "east": -39.7313, "geometry": ["POINT(-67.23435 -68.2063)"], "keywords": "Antarctica; Atmosphere; Climate; Glaciers/ice Sheet; Glaciers/Ice Sheet; Glaciology; Meteorology; Model", "locations": "Antarctica", "north": -56.9464, "nsf_funding_programs": null, "persons": "Tedesco, Marco", "project_titles": "Enhanced Spatial Resolution Surface Melting over the Antarctic Peninsula (1958 - to date) from a Regional Climate Model Validated through Remote Sensing Observations", "projects": [{"proj_uid": "p0000313", "repository": "USAP-DC", "title": "Enhanced Spatial Resolution Surface Melting over the Antarctic Peninsula (1958 - to date) from a Regional Climate Model Validated through Remote Sensing Observations"}], "repo": "USAP-DC", "repositories": "USAP-DC", "science_programs": null, "south": -79.4662, "title": "Enhanced Spatial Resolution Surface Melting over the Antarctic Peninsula (1958 - to date) from a Regional Climate Model Validated through Remote Sensing Observations", "uid": "600160", "west": -94.7374}]
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| Dataset Title/Abstract/Map | NSF Award(s) | Date Created | PIs / Scientists | Project Links | Abstract | Bounds Geometry | Geometry | Selected | Visible |
|---|---|---|---|---|---|---|---|---|---|
|
Surface melt-related multi-source remote-sensing and climate model data over Helheim Glacier, Greenland for segmentation and machine learning applications
|
2136938 |
2024-10-07 | Alexander, Patrick; Antwerpen, Raphael; Cervone, Guido; Fettweis, Xavier; Lütjens, Björn; Tedesco, Marco |
Collaborative Research: EAGER: Generation of high resolution surface melting maps over Antarctica using regional climate models, remote sensing and machine learning |
This dataset contains high-resolution satellite-derived snow/ice surface melt-related data on a common 100 m equal area grid (Albers equal area projection; EPSG 9822) over Helheim Glacier and surrounding areas in Greenland. The data is used as part of a machine learning framework that aims to fill data gaps in computed meltwater fraction on the 100 m grid using a range of methods, results of which will be published separately. <br/><br/> <br/><br/>The data include fraction of a grid cell covered by meltwater derived from Sentinel-1 synthetic aperture radar (SAR) backscatter, satellite-derived passive microwave (PMW) brightness temperatures, snowpack liquid water content within the first meter of snow and atmospheric and radiative variables from the Modéle Atmosphérique Règional (MAR) regional climate model, spectral reflectance in four wavelength bands from the Moderate Resolution Imaging Spectroradiometer (MODIS), a static digital elevation model (DEM), and an ice sheet mask. <br/><br/>A similar dataset has also been produced for Larsen C ice shelf and is also available through the US Antarctic Program Data Center. <br/><br/> <br/><br/> <br/><br/> | ["POLYGON((-40 67.55,-39.611 67.55,-39.222 67.55,-38.833 67.55,-38.444 67.55,-38.055 67.55,-37.666 67.55,-37.277 67.55,-36.888 67.55,-36.499 67.55,-36.11 67.55,-36.11 67.28999999999999,-36.11 67.03,-36.11 66.77,-36.11 66.51,-36.11 66.25,-36.11 65.99,-36.11 65.73,-36.11 65.47,-36.11 65.21000000000001,-36.11 64.95,-36.499 64.95,-36.888 64.95,-37.277 64.95,-37.666 64.95,-38.055 64.95,-38.444 64.95,-38.833 64.95,-39.222 64.95,-39.611 64.95,-40 64.95,-40 65.21000000000001,-40 65.47,-40 65.73,-40 65.99,-40 66.25,-40 66.51,-40 66.77,-40 67.03,-40 67.28999999999999,-40 67.55))"] | ["POINT(-38.055 66.25)"] | false | false |
|
Surface melt-related multi-source remote-sensing and climate model data over Larsen C Ice Shelf, Antarctica for segmentation and machine learning applications
|
2136938 |
2024-10-07 | Alexander, Patrick; Antwerpen, Raphael; Cervone, Guido; Fettweis, Xavier; Lütjens, Björn; Tedesco, Marco |
Collaborative Research: EAGER: Generation of high resolution surface melting maps over Antarctica using regional climate models, remote sensing and machine learning |
This dataset contains high-resolution satellite-derived snow/ice surface melt-related data on a common 100 m equal area grid (Lambert azimuthal equal area projection; EPSG 9820) over Larsen C Ice Shelf and surrounding areas in Antarctica. The data is prepared to be used as part of a machine learning framework that aims to fill data gaps in computed meltwater fraction on the 100 m grid using a range of methods, results of which will be published separately. <br/><br/><br/>The data include fraction of a grid cell covered by meltwater derived from Sentinel-1 synthetic aperture radar (SAR) backscatter, satellite-derived passive microwave (PMW) brightness temperatures, snowpack liquid water content within the first meter of snow and atmospheric and radiative variables from the Modéle Atmosphérique Règional (MAR) regional climate model, a static digital elevation model (DEM), and an ice sheet mask. <br/><br/><br/>A similar dataset has been produced for Helheim Glacier, Greenland and is also available through the US Antarctic Program Data Center. | ["POLYGON((-68.5 -65.25,-67.35 -65.25,-66.2 -65.25,-65.05 -65.25,-63.9 -65.25,-62.75 -65.25,-61.6 -65.25,-60.45 -65.25,-59.3 -65.25,-58.15 -65.25,-57 -65.25,-57 -65.652,-57 -66.054,-57 -66.456,-57 -66.858,-57 -67.25999999999999,-57 -67.66199999999999,-57 -68.064,-57 -68.466,-57 -68.868,-57 -69.27,-58.15 -69.27,-59.3 -69.27,-60.45 -69.27,-61.6 -69.27,-62.75 -69.27,-63.9 -69.27,-65.05 -69.27,-66.2 -69.27,-67.35 -69.27,-68.5 -69.27,-68.5 -68.868,-68.5 -68.466,-68.5 -68.064,-68.5 -67.66199999999999,-68.5 -67.25999999999999,-68.5 -66.858,-68.5 -66.456,-68.5 -66.054,-68.5 -65.652,-68.5 -65.25))"] | ["POINT(-62.75 -67.25999999999999)"] | false | false |
|
Enhanced Spatial Resolution Surface Melting over the Antarctic Peninsula (1958 - to date) from a Regional Climate Model Validated through Remote Sensing Observations
|
1141973 |
2016-01-01 | Tedesco, Marco |
Enhanced Spatial Resolution Surface Melting over the Antarctic Peninsula (1958 - to date) from a Regional Climate Model Validated through Remote Sensing Observations |
This award supports a project to generate first-time validated enhanced spatial resolution (5-10 km) maps of surface melting over the Antarctic Peninsula for the period 1958 - to date from the outputs of a regional climate model and different downscaling techniques. These maps will be assessed and validated through new high spatial resolution (2.25 km) surface melting maps obtained from the QuikSCAT satellite for the period 1999 - 2009. The intellectual merit of this work is that it would be the first time that the outputs of a regional climate model would be used to study surface melting over Antarctica at such high spatial resolution and the first time that such results are validated by means of an observational tool that has such a large spatial coverage and high spatial resolution. The results generated in this study would also provide a first-time opportunity to study the melt distribution over the Peninsula and its correlation with climate drivers, such as the Southern Annual Mode (SAM) and the El Nino-Southern Oscillation (ENSO) at these unprecedented spatial scales. The enhanced resolution melting maps will also offer a unique opportunity to study melting trends and patterns over specific regions of the Peninsula, such as the Wilkins and the Larsen A and B ice shelves and evaluate whether the extreme melting observed during the recent collapses was unprecedented over the + 50 years. The broader impacts of the project are that it will integrate research and education by fully supporting one female undergrad student, a PhD student and partially supporting a PostDoc. The work will be done at a minority-serving institution and the PhD student who worked on the development of the high-resolution melting data set from QuikSCAT will become the PostDoc who will work on this project. Teaching and learning will be supported by incorporating research results into graduate and undergrad level courses and will be disseminated over the web and through appropriate channels. Results from this project will also benefit the society at large as they will improve our understanding of the links between atmospheric patterns and surface melting and they will contribute to improving estimates of sea level rise from the Antarctica continent. | ["POLYGON((-94.7374 -56.9464,-89.23679 -56.9464,-83.73618 -56.9464,-78.23557 -56.9464,-72.73496 -56.9464,-67.23435 -56.9464,-61.73374 -56.9464,-56.23313 -56.9464,-50.73252 -56.9464,-45.23191 -56.9464,-39.7313 -56.9464,-39.7313 -59.19838,-39.7313 -61.45036,-39.7313 -63.70234,-39.7313 -65.95432,-39.7313 -68.2063,-39.7313 -70.45828,-39.7313 -72.71026,-39.7313 -74.96224,-39.7313 -77.21422,-39.7313 -79.4662,-45.23191 -79.4662,-50.73252 -79.4662,-56.23313 -79.4662,-61.73374 -79.4662,-67.23435 -79.4662,-72.73496 -79.4662,-78.23557 -79.4662,-83.73618 -79.4662,-89.23679 -79.4662,-94.7374 -79.4662,-94.7374 -77.21422,-94.7374 -74.96224,-94.7374 -72.71026,-94.7374 -70.45828,-94.7374 -68.2063,-94.7374 -65.95432,-94.7374 -63.70234,-94.7374 -61.45036,-94.7374 -59.19838,-94.7374 -56.9464))"] | ["POINT(-67.23435 -68.2063)"] | false | false |
