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| Auteurs principaux: | , , , , |
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| Format: | Dataset Open Access |
| Langue: | en |
| Publié: |
PANGAEA
2021
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| Sujets: | |
| Accès en ligne: | https://doi.org/10.1594/PANGAEA.933874 |
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| _version_ | 1867171307040276480 |
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| author | Jutila, Arttu Hendricks, Stefan Ricker, Robert von Albedyll, Luisa Haas, Christian |
| author_facet | Jutila, Arttu Hendricks, Stefan Ricker, Robert von Albedyll, Luisa Haas, Christian |
| collection | Datos científicos de ciencias marinas y ambientales |
| contents | Airborne multi-instrument measurements of sea ice were made in April 2017 as part of the Polar Airborne Measurements and Arctic Regional Climate Model Simulation Project (PAMARCMIP) under the AWI IceBird campaign series. The data consist of four surveys spanning sea-ice covered areas in the Beaufort and Chukchi Seas. 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. |
| format | Dataset Open Access |
| id | pangaea_https___doi_org_10_1594_PANGAEA_933874 |
| institution | PANGAEA |
| language | en |
| publishDate | 2021 |
| publisher | PANGAEA |
| record_format | pangaea |
| spellingShingle | Airborne sea ice parameters during aircraft flight P5_205_PAMARCMIP_2017_1704041501, Version 1 Jutila, Arttu Hendricks, Stefan Ricker, Robert von Albedyll, Luisa Haas, Christian AC; Airborne electromagnetic (EM) induction sounding; Airborne Laserscanner (ALS) RIEGL VQ580; Airborne surveys to collect measurements of sea ice thickness in the Arctic; Airborne ultra-wideband radar; Aircraft; Arctic Ocean; AWI_IceBird; AWI_SeaIce; Calculated; Cryosphere; DATE/TIME; Density, ice; Density, ice, uncertainty; Ice type; Infrared radiation pyrometer, Heitronics, KT19.85II; LATITUDE; LONGITUDE; Number of observations; P5_205_PAMARCMIP_2017_1704041501; P5-205_PAMARCMIP_2017; PAMARCMIP; POLAR 5; 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; UWB Airborne multi-instrument measurements of sea ice were made in April 2017 as part of the Polar Airborne Measurements and Arctic Regional Climate Model Simulation Project (PAMARCMIP) under the AWI IceBird campaign series. The data consist of four surveys spanning sea-ice covered areas in the Beaufort and Chukchi Seas. 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. |
| title | Airborne sea ice parameters during aircraft flight P5_205_PAMARCMIP_2017_1704041501, Version 1 |
| topic | AC; Airborne electromagnetic (EM) induction sounding; Airborne Laserscanner (ALS) RIEGL VQ580; Airborne surveys to collect measurements of sea ice thickness in the Arctic; Airborne ultra-wideband radar; Aircraft; Arctic Ocean; AWI_IceBird; AWI_SeaIce; Calculated; Cryosphere; DATE/TIME; Density, ice; Density, ice, uncertainty; Ice type; Infrared radiation pyrometer, Heitronics, KT19.85II; LATITUDE; LONGITUDE; Number of observations; P5_205_PAMARCMIP_2017_1704041501; P5-205_PAMARCMIP_2017; PAMARCMIP; POLAR 5; 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; UWB |
| url | https://doi.org/10.1594/PANGAEA.933874 |