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  • 04.03. Geodesy  (1)
  • 20191002_01; 20191020_01; 20191029_01; 20191105_01; 20191112_01; 20191112_02; 20191119_01; 20191130_01; 20191206_01; 20191224_01; 20191225_01; 20191228_01; 20191230_01; 20200107_01; 20200107_02; 20200108_01; 20200108_03; 20200108_04; 20200116_01; 20200116_02; 20200121_01; 20200123_01; 20200123_02; 20200125_01; 20200128_01; 20200202_01; 20200204_01; 20200209_01; 20200212_01; 20200217_01; 20200217_02; 20200227_01; 20200321_01; 20200321_02; 20200423_01; Airborne laser scanning; Arctic; Arctic Ocean; HELI; Helicopter; IceSense; MOSAiC; MOSAiC20192020; MOSAIC-HELI; Multidisciplinary drifting Observatory for the Study of Arctic Climate; Polarstern; PS122_1_2_45_2019092801; PS122_4_44_27_2020061101; PS122_4_44_65_2020061502; PS122_4_44_78_2020061601; PS122_4_45_112_2020070401; PS122_4_45_36_2020063001; PS122_4_45_37_2020063002; PS122_4_46_36_2020070701; PS122_4_46_39_2020070703; PS122_4_46_97_2020071101; PS122_4_47_96_2020071701; PS122_4_48_69_2020072201; PS122_4_50_32_2020080601; PS122_4_50_45_2020080701; PS122/1; PS122/1_10-78; PS122/1_2-167; PS122/1_2-45; PS122/1_2-57; PS122/1_5-9; PS122/1_6-11; PS122/1_7-24; PS122/1_7-25; PS122/1_8-23; PS122/1_9-98; PS122/2; PS122/2_17-101; PS122/2_17-98; PS122/2_17-99; PS122/2_18-7; PS122/2_19-44; PS122/2_19-45; PS122/2_19-46; PS122/2_19-51; PS122/2_19-52; PS122/2_19-53; PS122/2_20-52; PS122/2_20-53; PS122/2_21-122; PS122/2_21-41; PS122/2_21-77; PS122/2_21-78; PS122/2_22-16; PS122/2_22-97; PS122/2_23-109; PS122/2_23-14; PS122/2_24-31; PS122/2_25-7; PS122/2_25-8; PS122/3; PS122/3_29-49; PS122/3_32-42; PS122/3_32-70; PS122/3_32-71; PS122/3_33-17; PS122/3_35-48; PS122/3_35-49; PS122/3_37-63; PS122/3_37-66; PS122/3_39-109; PS122/4; PS122/4_44-27; PS122/4_44-65; PS122/4_44-78; PS122/4_45-112; PS122/4_45-36; PS122/4_45-37; PS122/4_46-36; PS122/4_46-39; PS122/4_46-97; PS122/4_47-96; PS122/4_48-69; PS122/4_50-32; PS122/4_50-45; PS122/5; PS122/5_59-139; PS122/5_61-190; PS122/5_61-62; PS122/5_61-63; PS122/5_62-166; PS122/5_62-67; PS122/5_63-118; PS122/5_63-3; Remote Sensing of the Seasonal Evolution of Climate-relevant Sea Ice Properties; Sea ice; Surface Elevation  (1)
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Years
  • 1
    Publication Date: 2024-04-24
    Description: This data set provides high-resolution geolocated point clouds of sea-ice or snow surface elevation for mapping temporal and spatial evolution of sea-ice conditions such as freeboard, roughness, or the size and spatial distributions of surface features. The surface elevation data are referenced to the DTU21 mean sea surface height and are not corrected for sea-ice drift during acquisition. The data were collected using a near-infrared, line-scanning Riegl VQ-580 airborne laser scanner (hdl:10013/sensor.7ebb63c3-dc3b-4f0f-9ca5-f1c6e5462a31 & hdl:10013/sensor.7a931b33-72ca-46d0-b623-156836ac9550) mounted in a helicopter along the MOSAiC drift from the north of the Laptev Sea, across the central Arctic Ocean, and towards the Fram Strait from September 2019 to October 2020. The flights are both small scale, ~5x5 km grid patterns mainly over the central observatory, and large scale, few tens of km away from RV Polarstern, triangle patterns, or transects. The point cloud data are stored in 5-min along-track segments in a custom binary format, for which we provide a python-based parsing tool in awi-als-toolbox (https://github.com/awi-als-toolbox/awi-als-toolbox), together with corresponding metadata json and line-shot quicklook png files. The point cloud data includes as variables: surface elevation (referenced to DTU mean sea surface height), surface reflectance, and echo width. The degraded GPS altitude data 〉85°N may cause undulations in the along-track surface elevations, which are not corrected for in this data product.
    Keywords: 20191002_01; 20191020_01; 20191029_01; 20191105_01; 20191112_01; 20191112_02; 20191119_01; 20191130_01; 20191206_01; 20191224_01; 20191225_01; 20191228_01; 20191230_01; 20200107_01; 20200107_02; 20200108_01; 20200108_03; 20200108_04; 20200116_01; 20200116_02; 20200121_01; 20200123_01; 20200123_02; 20200125_01; 20200128_01; 20200202_01; 20200204_01; 20200209_01; 20200212_01; 20200217_01; 20200217_02; 20200227_01; 20200321_01; 20200321_02; 20200423_01; Airborne laser scanning; Arctic; Arctic Ocean; HELI; Helicopter; IceSense; MOSAiC; MOSAiC20192020; MOSAIC-HELI; Multidisciplinary drifting Observatory for the Study of Arctic Climate; Polarstern; PS122_1_2_45_2019092801; PS122_4_44_27_2020061101; PS122_4_44_65_2020061502; PS122_4_44_78_2020061601; PS122_4_45_112_2020070401; PS122_4_45_36_2020063001; PS122_4_45_37_2020063002; PS122_4_46_36_2020070701; PS122_4_46_39_2020070703; PS122_4_46_97_2020071101; PS122_4_47_96_2020071701; PS122_4_48_69_2020072201; PS122_4_50_32_2020080601; PS122_4_50_45_2020080701; PS122/1; PS122/1_10-78; PS122/1_2-167; PS122/1_2-45; PS122/1_2-57; PS122/1_5-9; PS122/1_6-11; PS122/1_7-24; PS122/1_7-25; PS122/1_8-23; PS122/1_9-98; PS122/2; PS122/2_17-101; PS122/2_17-98; PS122/2_17-99; PS122/2_18-7; PS122/2_19-44; PS122/2_19-45; PS122/2_19-46; PS122/2_19-51; PS122/2_19-52; PS122/2_19-53; PS122/2_20-52; PS122/2_20-53; PS122/2_21-122; PS122/2_21-41; PS122/2_21-77; PS122/2_21-78; PS122/2_22-16; PS122/2_22-97; PS122/2_23-109; PS122/2_23-14; PS122/2_24-31; PS122/2_25-7; PS122/2_25-8; PS122/3; PS122/3_29-49; PS122/3_32-42; PS122/3_32-70; PS122/3_32-71; PS122/3_33-17; PS122/3_35-48; PS122/3_35-49; PS122/3_37-63; PS122/3_37-66; PS122/3_39-109; PS122/4; PS122/4_44-27; PS122/4_44-65; PS122/4_44-78; PS122/4_45-112; PS122/4_45-36; PS122/4_45-37; PS122/4_46-36; PS122/4_46-39; PS122/4_46-97; PS122/4_47-96; PS122/4_48-69; PS122/4_50-32; PS122/4_50-45; PS122/5; PS122/5_59-139; PS122/5_61-190; PS122/5_61-62; PS122/5_61-63; PS122/5_62-166; PS122/5_62-67; PS122/5_63-118; PS122/5_63-3; Remote Sensing of the Seasonal Evolution of Climate-relevant Sea Ice Properties; Sea ice; Surface Elevation
    Type: Dataset
    Format: application/zip, 64 datasets
    Location Call Number Limitation Availability
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  • 2
    Publication Date: 2019-01-25
    Description: Analysis | Published: 13 June 2018 Mass balance of the Antarctic Ice Sheet from 1992 to 2017 The IMBIE team Naturevolume 558, pages219–222 (2018) | Download Citation Abstract The Antarctic Ice Sheet is an important indicator of climate change and driver of sea-level rise. Here we combine satellite observations of its changing volume, flow and gravitational attraction with modelling of its surface mass balance to show that it lost 2,720 ± 1,390 billion tonnes of ice between 1992 and 2017, which corresponds to an increase in mean sea level of 7.6 ± 3.9 millimetres (errors are one standard deviation). Over this period, ocean-driven melting has caused rates of ice loss from West Antarctica to increase from 53 ± 29 billion to 159 ± 26 billion tonnes per year; ice-shelf collapse has increased the rate of ice loss from the Antarctic Peninsula from 7 ± 13 billion to 33 ± 16 billion tonnes per year. We find large variations in and among model estimates of surface mass balance and glacial isostatic adjustment for East Antarctica, with its average rate of mass gain over the period 1992–2017 (5 ± 46 billion tonnes per year) being the least certain.
    Description: Published
    Description: 219-222
    Description: 5A. Paleoclima e ricerche polari
    Description: JCR Journal
    Keywords: Antarctica ; Ice sheet mass balance ; 02.02. Glaciers ; 04.03. Geodesy
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
    Location Call Number Limitation Availability
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