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  • AWI_SeaIce; Sea Ice Physics @ AWI  (4)
  • AC; Airborne electromagnetic (EM) induction sounding; Airborne Laserscanner (ALS) RIEGL VQ580; Airborne surveys to collect measurements of sea ice thickness in the Arctic; Airborne ultrawideband radar; Aircraft; Arctic; Arctic Ocean; AWI_IceBird; AWI_SeaIce; Calculated; Cryosphere; DATE/TIME; Density, ice; Density, ice, uncertainty; Freeboard; Ice type; Infrared radiation pyrometer, Heitronics, KT19.85II; LATITUDE; LONGITUDE; Number of observations; P6_217_ICEBIRD_2019_1904071201; P6-217_ICEBIRD_2019; PAMARCMIP 2019; POLAR 6; Quality flag; Sea ice; Sea ice, age; Sea ice and snow thickness; Sea ice and snow thickness, uncertainty; Sea ice density; Sea ice freeboard; Sea Ice Physics @ AWI; Sea ice thickness; snow depth; Snow freeboard; Snow freeboard, maximum; Snow freeboard, minimum; Snow freeboard, standard deviation; Snow freeboard, uncertainty; Snow thickness; Snow thickness, maximum; Snow thickness, minimum; Snow thickness, standard deviation; Snow thickness, uncertainty; Surface temperature; Surface temperature, maximum; Surface temperature, minimum; Surface temperature, standard deviation  (2)
Document type
Keywords
Publisher
Years
  • 1
    Publication Date: 2023-05-12
    Description: Airborne observations of sea-ice plus snow thickness were made in August and September during POLARSTERN campaign ARK-XXVI/3 (TransArc) in the Arctic Ocean. The data record consists of 16 surveys in ice-covered part of the Arctic Ocean along the cruise track. For each helicopter survey, the geolocated thickness data from an airborne EM sensor is provided with a point spacing of approximately 4 meters. The thickness values of the EM-Bird include the snow layer, when snow is present on sea ice. Each thickness values represents the average thickness within an area of approximately 50 meters. Larger gaps in the thickness information are caused by regular high-altitude calibrations of the EM sensor. The data is routinely used to assess changes of the sea ice thickness trends in the Arctic Ocean and for sea-ice process studies that include the sea-ice thickness distribution.
    Keywords: AWI_SeaIce; Sea Ice Physics @ AWI
    Type: Dataset
    Format: application/zip, 16 datasets
    Location Call Number Limitation Availability
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  • 2
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    PANGAEA
    In:  Supplement to: Hunkeler, Priska A; Hoppmann, Mario; Hendricks, Stefan; Kalscheuer, Thomas; Gerdes, Rüdiger (2016): A glimpse beneath Antarctic landfast sea ice: platelet-layer volume from multi-frequency electromagnetic induction sounding. Geophysical Research Letters, 43(1), 222-231, https://doi.org/10.1002/2015GL065074
    Publication Date: 2023-03-16
    Description: Ice shelves strongly impact coastal Antarctic sea-ice and the associated ecosystem through the formation of a sub-sea-ice platelet layer. Although progress has been made in determining and understanding its spatio-temporal variability based on point measurements, an investigation of this phenomenon on a larger scale remains a challenge due to logistical constraints and a lack of suitable methodology. In this study, we applied a laterally-constrained Marquardt-Levenberg inversion to a unique multi-frequency electromagnetic (EM) induction sounding dataset obtained on the landfast sea ice of Atka Bay, eastern Weddell Sea, in 2012. In addition to consistent fast-ice thickness and -conductivities along 〉 100 km transects; we present the first comprehensive, high resolution platelet-layer thickness and -conductivity dataset recorded on Antarctic sea ice. The reliability of the algorithm was confirmed by using synthetic data, and the inverted platelet-layer thicknesses agreed within the data uncertainty to drill-hole measurements. Ice-volume fractions were calculated from platelet-layer conductivities, revealing that an older and thicker platelet layer is denser and more compacted than a loosely attached, young platelet layer. The overall platelet-layer volume below Atka Bay fast ice suggests that the contribution of ocean/ice-shelf interaction to sea-ice volume in this region is even higher than previously thought. This study also implies that multi-frequency EM induction sounding is an effective approach in determining platelet layer volume on a larger scale than previously feasible. When applied to airborne multi-frequency EM, this method could provide a step towards an Antarctic-wide quantification of ocean/ice-shelf interaction.
    Keywords: AWI_SeaIce; Sea Ice Physics @ AWI
    Type: Dataset
    Format: application/zip, 13 datasets
    Location Call Number Limitation Availability
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  • 3
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    PANGAEA
    In:  Supplement to: Nicolaus, Marcel; Katlein, Christian; Maslanik, James A; Hendricks, Stefan (2012): Changes in Arctic sea ice result in increasing light transmittance and absorption. Geophysical Research Letters, 39(24), L24501, https://doi.org/10.1029/2012GL053738
    Publication Date: 2023-03-16
    Description: Arctic sea ice has declined and become thinner and younger (more seasonal) during the last decade. One consequence of this is that the surface energy budget of the Arctic Ocean is changing. While the role of surface albedo has been studied intensively, it is still widely unknown how much light penetrates through sea ice into the upper ocean, affecting sea-ice mass balance, ecosystems, and geochemical processes. Here we present the first large-scale under-ice light measurements, operating spectral radiometers on a remotely operated vehicle (ROV) under Arctic sea ice in summer. This data set is used to produce an Arctic-wide map of light distribution under summer sea ice. Our results show that transmittance through first-year ice (FYI, 0.11) was almost three times larger than through multi-year ice (MYI, 0.04), and that this is mostly caused by the larger melt-pond coverage of FYI (42 vs. 23%). Also energy absorption was 50% larger in FYI than in MYI. Thus, a continuation of the observed sea-ice changes will increase the amount of light penetrating into the Arctic Ocean, enhancing sea-ice melt and affecting sea-ice and upper-ocean ecosystems.
    Keywords: AWI_SeaIce; Sea Ice Physics @ AWI
    Type: Dataset
    Format: application/zip, 54 datasets
    Location Call Number Limitation Availability
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  • 4
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    PANGAEA
    In:  Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven
    Publication Date: 2023-07-03
    Description: This dataset was created via processing of raw position data acquired by the GPS sensor for scientific equipment on Polar 6/Polar 5 to receive a validated master track which is used as reference of further expedition data.
    Keywords: AWI_SeaIce; Sea Ice Physics @ AWI
    Type: Dataset
    Format: application/zip, 16 datasets
    Location Call Number Limitation Availability
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  • 5
    Publication Date: 2024-05-17
    Description: Airborne multi-instrument measurements of sea ice were made in April 2019 during the winter campaign of the AWI IceBird campaign series. The data consist of five surveys spanning sea-ice covered areas in the Lincoln Sea, Central Arctic Ocean, as well as the Beaufort Sea. For each flight, the geolocated total (ice+snow) thickness data from an airborne electromagnetic (EM) induction sensor are provided with a point spacing of approximately 5-6 meters. Larger gaps in the trajectories arise from high-altitude calibrations of the EM sensor. The data are combined with collocated and simultaneous snow depth measurements from an airborne frequency-modulated continuous-wave ultrawideband radar, snow freeboard measurements from an airborne near-infrared laser scanner, and surface temperature measurements from an airborne infrared radiation pyrometer. Each value represents the average within the approximately 40 m diameter footprint of the EM sensor, thus representing a smoothed representation. These values are then used to derive further sea ice parameters such as sea ice bulk density. The trajectory data contain the full and unfiltered data record with quality flags.
    Keywords: AC; Airborne electromagnetic (EM) induction sounding; Airborne Laserscanner (ALS) RIEGL VQ580; Airborne surveys to collect measurements of sea ice thickness in the Arctic; Airborne ultrawideband radar; Aircraft; Arctic; Arctic Ocean; AWI_IceBird; AWI_SeaIce; Calculated; Cryosphere; DATE/TIME; Density, ice; Density, ice, uncertainty; Freeboard; Ice type; Infrared radiation pyrometer, Heitronics, KT19.85II; LATITUDE; LONGITUDE; Number of observations; P6_217_ICEBIRD_2019_1904071201; P6-217_ICEBIRD_2019; PAMARCMIP 2019; POLAR 6; Quality flag; Sea ice; Sea ice, age; Sea ice and snow thickness; Sea ice and snow thickness, uncertainty; Sea ice density; Sea ice freeboard; Sea Ice Physics @ AWI; Sea ice thickness; snow depth; Snow freeboard; Snow freeboard, maximum; Snow freeboard, minimum; Snow freeboard, standard deviation; Snow freeboard, uncertainty; Snow thickness; Snow thickness, maximum; Snow thickness, minimum; Snow thickness, standard deviation; Snow thickness, uncertainty; Surface temperature; Surface temperature, maximum; Surface temperature, minimum; Surface temperature, standard deviation
    Type: Dataset
    Format: text/tab-separated-values, 1872487 data points
    Location Call Number Limitation Availability
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  • 6
    Publication Date: 2024-05-17
    Description: Airborne multi-instrument measurements of sea ice were made in April 2019 during the winter campaign of the AWI IceBird campaign series. The data consist of five surveys spanning sea-ice covered areas in the Lincoln Sea, Central Arctic Ocean, as well as the Beaufort Sea. For each flight, the geolocated total (ice+snow) thickness data from an airborne electromagnetic (EM) induction sensor are provided with a point spacing of approximately 5-6 meters. Larger gaps in the trajectories arise from high-altitude calibrations of the EM sensor. The data are combined with collocated and simultaneous snow depth measurements from an airborne frequency-modulated continuous-wave ultrawideband radar, snow freeboard measurements from an airborne near-infrared laser scanner, and surface temperature measurements from an airborne infrared radiation pyrometer. Each value represents the average within the approximately 40 m diameter footprint of the EM sensor, thus representing a smoothed representation. These values are then used to derive further sea ice parameters such as sea ice bulk density. The trajectory data contain the full and unfiltered data record with quality flags.
    Keywords: AC; Airborne electromagnetic (EM) induction sounding; Airborne Laserscanner (ALS) RIEGL VQ580; Airborne surveys to collect measurements of sea ice thickness in the Arctic; Airborne ultrawideband radar; Aircraft; Arctic; Arctic Ocean; AWI_IceBird; AWI_SeaIce; Calculated; Cryosphere; DATE/TIME; Density, ice; Density, ice, uncertainty; Freeboard; Ice type; Infrared radiation pyrometer, Heitronics, KT19.85II; LATITUDE; LONGITUDE; Number of observations; P6_217_ICEBIRD_2019_1904071201; P6-217_ICEBIRD_2019; PAMARCMIP 2019; POLAR 6; Quality flag; Sea ice; Sea ice, age; Sea ice and snow thickness; Sea ice and snow thickness, uncertainty; Sea ice density; Sea ice freeboard; Sea Ice Physics @ AWI; Sea ice thickness; snow depth; Snow freeboard; Snow freeboard, maximum; Snow freeboard, minimum; Snow freeboard, standard deviation; Snow freeboard, uncertainty; Snow thickness; Snow thickness, maximum; Snow thickness, minimum; Snow thickness, standard deviation; Snow thickness, uncertainty; Surface temperature; Surface temperature, maximum; Surface temperature, minimum; Surface temperature, standard deviation
    Type: Dataset
    Format: text/tab-separated-values, 1872487 data points
    Location Call Number Limitation Availability
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