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42 results for “ground ice”
Amery Ice Shelf Grounding Line Datapoints Extraction from Airborne Ice-penetrating Radar
<p>We present a new grounding line product for Amery Ice Shelf - the ice-penetrating radar-derived grounding line points. The 137 grounding line points were identified by 53 survey lines from 2017 to 2020 and classified into three categories. The 'Class 1' points are extracted by significant echo reflection changes between ice-bed and ice-seawater interfaces along survey lines with continuous signal and have the highest accuracy. The 'Class2' and 'Class 3' points were derived from survey lines with 'fuzzy region' with lower accuracy. The mean interval of radar-derived points is 16.4 km. The 'best case' radar-derived positions (Class 1) and those from satellite data reveals a mean separation of 1.00±1.16 km. Two products are available: (1) ice thickness data of Amery Ice Shelf from ice-penetrating radar lines; (2) radar-derived grounding line position (137 points). The ice thickness was calculated by ice surface and bottom signal and the unit is m. The radar-derived grounding line position have six fields, latitude, longitude, id, ice thickness, date (for collecting the radar data) and Class (the category of point).</p>
Excess ground ice profiles from Sentinel 1
<p>Maps of excess ice content profiles were estimated from Sentinel-1 subsidence observations. Results for three study regions in Alaska are included:</p> <ul> <li>Happy Valley, Brooks Foothills</li> <li>Ice Cut, Brooks Foothills</li> <li>Kivalina, Northwestern Alaska</li> </ul> <p>The results for each region are contained in the corresponding .zip file. The subfolders correspond to the different years. The content of each subfolder are as follows:</p> <ul> <li>meta.txt: human-readable metadata: geolocation information (rasterio affine transformation, projection, size of image, vertical grid [m])</li> <li>e_mean.npy: array containing the posterior mean of the excess ground ice profiles e [-]</li> <li>e_quantile.npy: array containing the 10th and 90th posterior percentile of the excess ground ice profiles e [-]</li> </ul> <p> </p>
Data from: Ground ice melt in the high Arctic leads to greater ecological heterogeneity
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Data for: Grounding zone of Amery Ice Shelf, Antarctica, from differential synthetic-aperture radar interferometry
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Kivalina ground ice map
<p>Ground ice classification for a ~ 65 km<sup>2 </sup>area near Kivalina, Northwest Alaska.</p> <p>Source: Manual image interpretation, field notes</p> <p> </p> <p>Code:</p> <p>0: ice poor | 1: ice rich | 2: indeterminate | 3: infrastructure</p> <p>Include: Included in comparison with late-season subsidence</p> <p>0: No | 1: Yes</p>
Parameter files and code for simulations in "Simulating the effect of subsurface drainage on the thermal regime and ground ice in blocky terrain, Norway"
<p>This upload contains the source code, the run files and the parameter files for the simulations in the manuscript "Simulating the effect of subsurface drainage on the thermal regime and ground ice in blocky terrain, Norway" (submitted to ESD).</p> <p>Instructions are provided in the README.txt files.</p>
Ground Penetrating Radar (GPR) survey of four artificial ice reservoirs (icestupas)
<p><strong>Objective</strong></p> <p>The objective of this project is to establish that non–invasive subsurface imaging with ground penetrating radar (GPR) is a viable method to map internal structure of artificial ice reservoirs(AIR) and to estimate volume. Particular objectives were the following:</p> <ol> <li><strong>Volume validation : </strong>GPR surveys could be used to validate volumes of AIRs.</li> <li><strong>Spatial density resolution : </strong>GPR data could help identify air, snow and ice layers within the AIR.</li> </ol> <p><strong>GPR Field Work</strong></p> <p>GPR survey has been conducted on four Ice Stupas at locations namely Phaterak, Gangles, Kullum and Takmachik in March 2020 as part of an <a href="https://swisspolar.ch/2021/05/artificial-ice-reservoirs-of-ladakh-suryanarayanan-balasubramanian/">Swiss Polar Institute funded expedition</a>.</p> <p><strong>Why Ground Penetrating Radar?</strong></p> <p>Ice is very transparent to GPR signals, allowing tremendous penetration. GPR is also sensitive to subtle changes in the properties of ice layers. This makes it a powerful tool to image the internal structure of glaciers and ice sheets at a scale of meters or hundreds of meters. The basic principle of a pulsed GPR system is to send an electromagnetic signal into the ground and to record the signal reflections as a function of their two-way travel time. Partial reflections of the electromagnetic wave recorded as internal reflection horizons (IRH) occur at vertical discontinuities in the dielectric material. From polar studies, IRH are known to coincide with variations in density, acidity (Robin et al., 1969), liquid water content (Forster et al., 2014) and changes in crystal orientation fabric.</p> <p><strong>Archive contents</strong></p> <p>The archives contents are organized in four separate directories. Each directory contains GPR data of one icestupa. Apart from this, a preliminary report is also attached produced by the GPR company (SHIJAY PROJECTS).</p>
GPM Ground Validation Autonomous Parsivel Unit (APU) ICE POP V1
The GPM Ground Validation Autonomous Parsivel Unit (APU) ICE POP dataset was collected during the International Collaborative Experiments for Pyeongchang 2018 Olympic and Paralympic Winter Games (ICE POP) field campaign in South Korea. The two major objectives of ICE POP were to study severe winter weather events in regions of complex terrain and improve the short-term forecasting of such events. These data contributed to Global Precipitation Measurements mission Ground Validation (GPM GV) campaign efforts to improve satellite estimates of orographic winter precipitation. This dataset consists of precipitation data including precipitation amount, precipitation rate, reflectivity in Rayleigh regime, liquid water content, drop diameter, and drop concentration. Data are available in ASCII format from October 31, 2015 through July 1, 2018. It should be noted that this dataset extends prior to the field campaign.
GPM Ground Validation Precipitation Imaging Package (PIP) ICE POP V1
The GPM Ground Validation Precipitation Imaging Package (PIP) ICE POP dataset includes precipitation measurements and video images collected by the Precipitation Imaging Package (PIP) during the International Collaborative Experiments for Pyeongchang 2018 Olympic and Paralympic Winter Games (ICE-POP) field campaign in South Korea. The two major objectives of ICE-POP were to study severe winter weather events in regions of complex terrain and improve the short-term forecasting of such events. These data contributed to the Global Precipitation Measurement mission Ground Validation (GPM GV) campaign efforts to improve satellite estimates of orographic winter precipitation. Data values obtained using PIP measurements include particle size distributions, fall velocity distributions, precipitation density estimates, and precipitation rates. The dataset files are available from June 18, 2017 through December 30, 2018 as generic data files (.dat) in ASCII-CSV format with browse imagery and video available in PNG and AVI format.
Ice-penetrating radar data used in paper "Evaluating and locating a suitable bedrock drilling site near Zhongshan Station with airborne and ground-based observations"
<p>These are the ice-penetrating radar data used in Figure 4 of the paper "Evaluating and locating a suitable bedrock drilling site near Zhongshan Station with airborne and ground-based observations".</p> <p>The"read_image.m" file can be used to re-display Figure 4(a) of the paper, where the "x.mat", "y.mat", and "radar_profile_data.mat" are the x and y coordinates of the survey line, and the return power of the ice-penetrating radar data, respectively.</p> <p>The "Data_of_profile_A-A'(Figure_4b).xlsx" file includes two sheets. One is the "subglacial topography" sheet, which includes information about longitude, latitude, ice thickness, bed elevation, and hydraulic potential along the profile A-A'. The other sheet is the "BRP" sheet, which includes information about bed reflection power along the profile A-A'.</p>
InSAR estimates of excess ground ice concentrations near the permafrost table, Kivalina, Alaska, USA
<p>Each subfolder contains the posterior mean and variance of excess ice concentrations [dimensionless] near the permafrost table estimated from Sentinel-1 InSAR, stored as a geotiff file. The folders correspond to four different estimation configurations:</p> <table> <tbody> <tr> <td>name</td> <td>year</td> <td>ebar period</td> <td>input data</td> </tr> <tr> <td>baseline</td> <td>2019</td> <td>(900 ◦C d, 2019-09-15)</td> <td>2019-06-06 – 2019-08-29</td> </tr> <tr> <td>later ebar</td> <td>2019</td> <td>(1000 ◦C d, 2019-09-15)</td> <td>2019-06-06 – 2019-08-29</td> </tr> <tr> <td>extra scene</td> <td>2019</td> <td>(900 ◦C d, 2019-09-15)</td> <td>2019-06-06 – 2019-09-10</td> </tr> <tr> <td>2018</td> <td>2018</td> <td>(900 ◦C d, 2018-09-15)</td> <td>2018-06-11 – 2018-09-03</td> </tr> </tbody> </table>
Land Resources of Russia -- Maps of Permafrost and Ground Ice, Version 1
This data set includes maps of permafrost extent, permafrost temperature, the permafrost boundary, and ground ice thickness for all of Russia. The maps are ESRI Shapefiles, which were digitized from paper maps taken from the World Atlas of Snow and Ice Resources, 1997, Institute of Geography, Russian Academy of Sciences, Moscow, Russia. The scale of the source maps range from 1:20,000,000 to 1:40,000,000. Polygons were assigned attributes based on the classes used in the legends of the paper map.These data were extracted from a larger collection entitled Land Resources of Russia. Data and documentation © 2002 copyright International Institute for Applied Systems Analysis and the Russian Academy of Sciences.
GPM Ground Validation SEA FLUX ICE POP V1
The GPM Ground Validation SEA FLUX ICE POP dataset includes estimates of ocean surface latent and sensible heat fluxes, 10m wind speed, 10m air temperature, 10m air humidity, and skin sea surface temperature in support of the International Collaborative Experiments for Pyeongchang 2018 Olympic and Paralympic Winter Games (ICE-POP) field campaign in South Korea. The two major objectives of ICE-POP were to study severe winter weather events in regions of complex terrain and improve the short-term forecasting of such events. These data contributed to the Global Precipitation Measurement mission Ground Validation (GPM GV) campaign efforts to improve satellite estimates of orographic winter precipitation. This data file is available in netCDF-4 format from September 1, 2017 through April 30, 2018.
GPM GROUND VALIDATION SATELLITE SIMULATED ORBITS TWP-ICE V1
The GPM Ground Validation Satellite Simulated Orbits TWP-ICE dataset is available in the Orbital database, which takes account for the atmospheric profiles, the cloud/rain profiles, and the detailed surface/terrain information from the Cloud-Resolving Model (CRM) database. Unique geometry and antenna gain patterns of each sensor (GMI imager, GMI sounder, DPR Ku, DPR Ka_MA, DPR Ka_HS) are considered. The Orbital database consists of satellite orbit parameters, geolocation of Field of View and satellite location, and simulated Level 1B/Level 2-like parameters in satellite orbital grid. Orbital data covers a portion of sampling right over the Cloud-resolving model (CRM) domain. All orbital data format is NetCDF3, and it contains dimensions, parameter descriptions, and parameter units. Each project's data is distributed as a separate dataset. MC3E occurred in Oklahoma, USA in 2011; LPVEX took place in Finland in 2010; C3VP experiment was held in Canada in 2007 and TWP-ICE took place in Australia in 2006.
Ground temperatures in ice-cemented ground at Linnaeus Terrace, Dry Valleys, Antarctica, Version 1
Soil temperatures were measured with Campbell 107 soil thermistors. Thermistors were placed at 0, 17, 23 (just above the ice-cemented permafrost) and 40 cm depth. To emplace the sensors, first a soil pit was dug to the level of ice-cemented permafrost. Then a hammer drill was used to make a narrow, 15 cm deep hole into the ice-cemented ground. The thermistor was placed into the drill hole. This procedure caused minimal disturbance to the ice-cemented ground. Air temperature and humidity were measured with a Campbell 207 air probe. The temperature on the surface of an outcrop of Beacon sandstone was measured with a T-type thermocouple. Sunlight was measured with a LiCor 200 pyranometer. The sensors were deployed during Jan 1993 but (due to equipment failure) data storage began only on 6 Jan 1994 and was continued until 16 Jan 1995. All temperature sensors were removed after the data collection interval and calibrated in the laboratory. Calibrations were applied using the Steinhart and Hart (1968) representations for the temperature dependence of the thermistor resistance. This was necessary since the instrumental calibration for the 107 thermistor provided by Campbell did not extend below -40C. After correction, the error in the temperature measurement is estimated to be less than 0.2 C and error in the humidity measurement was Campbell 207 RH sensor has high errors for relative humidity values below 15% --- tending to systematically overestimate values by more than 10% humidity. The error in the averaged light measurement is less than 10 W/m2. All sensors were sampled once every 10 minutes and averages of three measurements were written to final memory every 30 minutes corresponding to 48 recordings each day. Data are stored in columns of ASCII data; entries are 1. Digital day of year in 1994 2. Air temperature 3. Air relative humidity 4. Sunlight, W/m2 5. Soil surface temperature 4. Sunlight, W/m2 5. Soil surface temperature 6. Temperature at 17 cm depth 7. Temperature at 23 cm depth 8. Temperature at 40 cm depth 9. Temperature on surface of rock Data are presented on the CAPS Version 1.0 CD-ROM, June 1998.
Circum-Arctic Map of Permafrost and Ground-Ice Conditions, Version 2
The Circum-Arctic permafrost and ground ice map is available via ftp in ESRI Shapefile format and Equal-Area Scalable Earth Grid (EASE-Grid) format. See the Format section for an explanation of the files provided via FTP.The circumpolar permafrost and ground ice data contribute to a unified international data set that depicts the distribution and properties of permafrost and ground ice in the Northern Hemisphere (20°N to 90°N). The re-gridded data set shows discontinuous, sporadic, or isolated permafrost boundaries. Permafrost extent is estimated in percent area (90-100 percent, 50-90 percent, 10-50 percent, <10 percent, and no permafrost). Relative abundance of ground ice in the upper 20 m is estimated in percent volume (>20 percent, 10-20 percent, <10 percent, and 0 percent). The data set also contains the location of subsea and relict permafrost. the gridded data are gridded at 12.5 km, 25 km, and 0.5 degree resolution. The shapefiles were derived from the original 1:10,000,000 paper map (Brown et al. 1997)Permafrost, or permanently frozen ground, is ground (soil, sediment, or rock) that remains at or below 0°C for at least two years (Permafrost Subcommittee, 1988). It occurs both on land and beneath offshore arctic continental shelves, and underlies about 22 percent of the Earth's land surface.For more information on the creation of the original map, see Heginbottom et al. (1993). The original paper map also includes information on the relative abundance of ice wedges, massive ice bodies and Pingos, ranges of permafrost temperature and thickness (Brown et al. 1997).
GPM Ground Validation Dual-frequency Dual-polarized Doppler Radar (D3R) ICE POP
The GPM Ground Validation Dual-frequency Dual-polarized Doppler Radar (D3R) ICE POP dataset includes reflectivity, differential reflectivity, copolar correlation coefficient, differential propagation phase, radial velocity, and spectrum width data collected by the Dual-frequency Dual-polarized Doppler Radar (D3R) during the International Collaborative Experiments for Pyeongchang 2018 Olympic and Paralympic Winter Games (ICE-POP) field campaign in South Korea. The two major objectives of ICE-POP were to study severe winter weather events in regions of complex terrain and improve the short-term forecasting of such events. These data contributed to Global Precipitation Measurement mission Ground Validation (GPM GV) campaign efforts to improve satellite estimates of orographic winter precipitation. The D3R was developed by a government-industry-academic consortium with funding from NASA's GPM Project. It operates at the ku (13.91 GHz ± 25 MHz) and ka (35.56 GHz ± 25 MHz) frequencies covering a fixed range from 450 m to 39.75 km. The D3R dataset files are available from November 1, 2017 through March 17, 2018 in netCDF-4 format.
GPM Ground Validation Micro Rain Radar (MRR) ICE POP V1
The GPM Ground Validation Micro Rain Radar (MRR) ICE POP dataset was collected during the International Collaborative Experiments for Pyeongchang 2018 Olympic and Paralympic Winter Games (ICE-POP) field campaign in South Korea. The two major objectives of ICE-POP were to study severe winter weather events in regions of complex terrain and improve the short-term forecasting of such events. These data contributed to Global Precipitation Measurement mission Ground Validation (GPM GV) campaign efforts to improve satellite estimates of orographic winter precipitation. This dataset consists of precipitation data collected by two MRR instruments from November 1, 2017 to March 1, 2018. These data are available in netCDF-3 and ASCII text formats.
MEaSUREs ITS_LIVE Antarctic Grounded Ice Sheet Elevation Change V001
This data product contains monthly ice sheet elevation change data for Antarctica derived from five radar altimetry missions (Geosat, ERS-1 and -2, Envisat and CryoSat-2) and two laser altimetry missions (ICESat and ICESat-2). Each time step and grid node includes relative error estimates and a quality flag that can be used to filter the data in space and time. The product is also provided with an estimate of static topography in the form of a digital elevation model (DEM), which was used to estimate monthly ice sheet elevation change. With a temporal coverage of 17 April 1985 to 16 December 2020, this product can be used to determine changes in ice sheet mass balance over time.
ICESat-2 L4 Grounding Zone for Antarctic Ice Shelves V001
This data set provides an Antarctic ice shelf grounding zone geolocation product, including the landward limit of ice flexure caused by ocean tidal movement (Point F), the seaward limit of ice flexure (Point H), and the break in surface slope (Point Ib) based on the ATLAS/ICESat-2 ATL06 Land Ice Height data set acquired between March 2019 and September 2020. The grounding zone estimates were derived from automated techniques using ICESat-2 repeat tracks.
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Allen Brain Atlas
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International Brain Laboratory public data
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OpenNeuro
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