USAP-DC

{"dp_type": "Dataset", "free_text": "Passive Microwave"}

[{"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": "Antarctica; Greenland; 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": "Larsen C Ice Shelf; Antarctica", "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": "1543432 Hock, Regine", "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))"], "date_created": "Tue, 22 Jun 2021 00:00:00 GMT", "description": "This dataset contains the total number of days per year with meltwater present at the surface across the Antarctic ice sheet and surrounding ice shelves derived from passive microwave satellite observations for each melt year from 1979/80 to 2019/20. This data comes from daily and near-daily SMMR, SSM/I, and SSMIS results at 25 km resolution at 19 GHz horizontal polarization. Each melt year starts on July 1 and ends June 30. The melt detection algorithm is described in Johnson and others (2020) and uses KMeans clustering analysis of the annual brightness temperature time series on each pixel to detect melt for that pixel and year. ", "east": 180.0, "geometry": ["POINT(0 -89.999)"], "keywords": "Antarctica; Glaciers/ice Sheet; Glaciers/Ice Sheet; Melt Days; Passive Microwave; Snow/ice; Snow/Ice; Surface Melt", "locations": "Antarctica; Antarctica", "north": -60.0, "nsf_funding_programs": "Antarctic Glaciology", "persons": "Johnson, Andrew; Hock, Regine; Fahnestock, Mark", "project_titles": "Collaborative Research: Present and Projected Future Forcings on Antarctic Peninsula Glaciers and Ice Shelves using the Weather Forecasting and Research (WRF) Model", "projects": [{"proj_uid": "p0010408", "repository": "USAP-DC", "title": "Collaborative Research: Present and Projected Future Forcings on Antarctic Peninsula Glaciers and Ice Shelves using the Weather Forecasting and Research (WRF) Model"}], "repo": "USAP-DC", "repositories": "USAP-DC", "science_programs": null, "south": -90.0, "title": "Antarctic passive microwave Kmeans derived surface melt days, 1979-2020", "uid": "601457", "west": -180.0}, {"awards": "1341547 Stroeve, Julienne", "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))"], "date_created": "Fri, 31 Aug 2018 00:00:00 GMT", "description": "Sea ice variability within the marginal ice zone (MIZ) and polynyas plays an important role for phytoplankton productivity and krill abundance. Therefore, mapping their spatial extent, seasonal and interannual variability is essential for understanding how current and future changes in these biologically active regions may impact the Antarctic marine ecosystem. Knowledge of the distribution of MIZ, consolidated pack ice and coastal polynyas to the total Antarctic sea ice cover may also help to shed light on the factors contributing towards recent expansion of the Antarctic ice cover in some regions and contraction in others. The long-term passive microwave 21 satellite data record provides the longest and most consistent record for assessing the proportion of the sea ice cover that is covered by each of these ice categories. This data set provides estimates of the MIZ, consolidated pack ice and polynyas from the NASA Team and Bootstrap sea ice concentration data sets, from 1979 to 2017.\r\n", "east": 180.0, "geometry": ["POINT(0 -89.999)"], "keywords": "Antarctica; Pack Ice; Polynya; Sea Ice; Southern Ocean", "locations": "Southern Ocean; Antarctica", "north": -60.0, "nsf_funding_programs": "Antarctic Organisms and Ecosystems", "persons": "Stroeve, Julienne", "project_titles": "Collaborative Research: Phytoplankton Phenology in the Antarctic: Drivers, Patterns, and Implications for the Adelie Penguin", "projects": [{"proj_uid": "p0000001", "repository": "USAP-DC", "title": "Collaborative Research: Phytoplankton Phenology in the Antarctic: Drivers, Patterns, and Implications for the Adelie Penguin"}], "repo": "USAP-DC", "repositories": "USAP-DC", "science_programs": null, "south": -90.0, "title": "Antarctic MIZ, Pack Ice and Polynya Maps from Passive Microwave Satellite Data", "uid": "601115", "west": -180.0}, {"awards": "0944653 Forster, Richard", "bounds_geometry": ["POLYGON((-119.4 -78.1,-118.46 -78.1,-117.52 -78.1,-116.58 -78.1,-115.64 -78.1,-114.7 -78.1,-113.76 -78.1,-112.82 -78.1,-111.88 -78.1,-110.94 -78.1,-110 -78.1,-110 -78.29,-110 -78.48,-110 -78.67,-110 -78.86,-110 -79.05,-110 -79.24,-110 -79.43,-110 -79.62,-110 -79.81,-110 -80,-110.94 -80,-111.88 -80,-112.82 -80,-113.76 -80,-114.7 -80,-115.64 -80,-116.58 -80,-117.52 -80,-118.46 -80,-119.4 -80,-119.4 -79.81,-119.4 -79.62,-119.4 -79.43,-119.4 -79.24,-119.4 -79.05,-119.4 -78.86,-119.4 -78.67,-119.4 -78.48,-119.4 -78.29,-119.4 -78.1))"], "date_created": "Thu, 01 Jan 2015 00:00:00 GMT", "description": "This award supports a project to broaden the knowledge of annual accumulation patterns over the West Antarctic Ice Sheet by processing existing near-surface radar data taken on the US ITASE traverse in 2000 and by gathering and validating new ultra/super-high-frequency (UHF) radar images of near surface layers (to depths of ~15 m), expanding abilities to monitor recent annual accumulation patterns from point source ice cores to radar lines. Shallow (15 m) ice cores will be collected in conjunction with UHF radar images to confirm that radar echoed returns correspond with annual layers, and/or sub-annual density changes in the near-surface snow, as determined from ice core stable isotopes. This project will additionally improve accumulation monitoring from space-borne instruments by comparing the spatial-radar-derived-annual accumulation time series to the passive microwave time series dating back over 3 decades and covering most of Antarctica. The intellectual merit of this project is that mapping the spatial and temporal variations in accumulation rates over the Antarctic ice sheet is essential for understanding ice sheet responses to climate forcing. Antarctic precipitation rate is projected to increase up to 20% in the coming century from the predicted warming. Accumulation is a key component for determining ice sheet mass balance and, hence, sea level rise, yet our ability to measure annual accumulation variability over the past 5 decades (satellite era) is mostly limited to point-source ice cores. Developing a radar and ice core derived annual accumulation dataset will provide validation data for space-born remote sensing algorithms, climate models and, additionally, establish accumulation trends. The broader impacts of the project are that it will advance discovery and understanding within the climatology, glaciology and remote sensing communities by verifying the use of UHF radars to monitor annual layers as determined by visual, chemical and isotopic analysis from corresponding shallow ice cores and will provide a dataset of annual to near-annual accumulation measurements over the past ~5 decades across WAIS divide from existing radar data and proposed radar data. By determining if temporal changes in the passive microwave signal are correlated with temporal changes in accumulation will help assess the utility of passive microwave remote sensing to monitor accumulation rates over ice sheets for future decades. The project will promote teaching, training and learning, and increase representation of underrepresented groups by becoming involved in the NASA History of Winter project and Thermochron Mission and by providing K-12 teachers with training to monitor snow accumulation and temperature here in the US, linking polar research to the student\u0027s backyard. The project will train both undergraduate and graduate students in polar research and will encouraging young investigators to become involved in careers in science. In particular, two REU students will participate in original research projects as part of this larger project, from development of a hypothesis to presentation and publication of the results. The support of a new, young woman scientist will help to increase gender diversity in polar research.\n", "east": -110.0, "geometry": ["POINT(-114.7 -79.05)"], "keywords": "Airborne Radar; Antarctica; Geology/Geophysics - Other; Glaciers/ice Sheet; Glaciers/Ice Sheet; Glaciology; Radar; WAIS Divide; WAIS Divide Ice Core", "locations": "Antarctica; WAIS Divide", "north": -78.1, "nsf_funding_programs": null, "persons": "Forster, Richard", "project_titles": "Collaborative Research: Annual satellite era accumulation patterns over WAIS Divide: A study using shallow ice cores, near-surface radars and satellites", "projects": [{"proj_uid": "p0000079", "repository": "USAP-DC", "title": "Collaborative Research: Annual satellite era accumulation patterns over WAIS Divide: A study using shallow ice cores, near-surface radars and satellites"}], "repo": "USAP-DC", "repositories": "USAP-DC", "science_programs": "WAIS Divide Ice Core", "south": -80.0, "title": "Annual Satellite Era Accumulation Patterns Over WAIS Divide: A Study Using Shallow Ice Cores, Near-Surface Radars and Satellites", "uid": "600146", "west": -119.4}, {"awards": "9526566 Bindschadler, Robert", "bounds_geometry": ["POINT(-174.45 -82.52)", "POINT(-119.4 -80.01)", "POINT(-84 -75.9)", "POINT(160.41 -74.21)"], "date_created": "Tue, 28 Nov 2006 00:00:00 GMT", "description": "This data set includes daily, monthly, and yearly mean surface air temperatures for four interior West Antarctic sites between 1978 and 1997. Data include air surface temperatures measured at the Byrd, Lettau, Lynn, and Siple Station automatic weather stations. In addition, because weather stations in Antarctica are difficult to maintain, and resulting multi-decade records are often incomplete, the investigators also calculated surface temperatures from satellite passive microwave brightness temperatures. Calibration of 37-GHz vertically polarized brightness temperature data during periods of known air temperature, using emissivity modeling, allowed the investigators to replace data gaps with calibrated brightness temperatures.\n\nMS Excel data files and GIF images derived from the data are available via ftp from the National Snow and Ice Data Center.", "east": 160.41, "geometry": ["POINT(-174.45 -82.52)", "POINT(-119.4 -80.01)", "POINT(-84 -75.9)", "POINT(160.41 -74.21)"], "keywords": "Antarctica; Atmosphere; Automated Weather Station; Meteorology; Temperature; West Antarctica", "locations": "West Antarctica; Antarctica", "north": -74.21, "nsf_funding_programs": "Antarctic Glaciology", "persons": "Shuman, Christopher A.; Stearns, Charles R.", "project_titles": "Passive Microwave Remote Sensing for Paleoclimate Indicators at Siple Dome, Antarctica", "projects": [{"proj_uid": "p0000191", "repository": "USAP-DC", "title": "Passive Microwave Remote Sensing for Paleoclimate Indicators at Siple Dome, Antarctica"}], "repo": "USAP-DC", "repositories": "USAP-DC", "science_programs": null, "south": -82.52, "title": "Decadal-Length Composite West Antarctic Air Temperature Records", "uid": "609097", "west": -174.45}]

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