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12,237 results for “2019”
TARP 2019: SU 2063 - SU 2065
Photogrammetric capture of stratigraphic units 2063-2065 Source: Objaverse 1.0 / Sketchfab
TARP 2019: SU 2084
Photogrammetric capture of stratigraphic unit 2084. Source: Objaverse 1.0 / Sketchfab
TARP 2019: SU 1044, SU 1060
Photogrammetric capture of stratigraphic units 1044, 1060 Source: Objaverse 1.0 / Sketchfab
TARP 2019: SU 2028 - SU 2032
Photogrammetric capture of stratigraphic units 2028-2032. Source: Objaverse 1.0 / Sketchfab
La ilusión de la Materia - Chile - 2019 - 18
Public sculpture after october 18, 2019, Santiago of Chile. Second version, after one week of the archive: "La ilusión de la Materia - Chile - 2019 - 1" https://skfb.ly/6OGAV Source: Objaverse 1.0 / Sketchfab
TARP 2019: SU 2066 - SU 2068
Photogrammetric capture of stratigraphic units 2066-2068 Source: Objaverse 1.0 / Sketchfab
TARP 2019: SU 1113
Photogrammetric capture of stratigraphic unit 1113 Source: Objaverse 1.0 / Sketchfab
TARP 2019: SU 2079
Photogrammetric capture of stratigraphic unit 2079 Source: Objaverse 1.0 / Sketchfab
TARP 2019: SU 2017
Photogrammetric capture of stratigraphic unit 2017 Source: Objaverse 1.0 / Sketchfab
TARP 2019: SU 1049 - SU 1055
Photogrammetric capture of stratigraphic units 1049 - 1055 Source: Objaverse 1.0 / Sketchfab
TARP 2019: SU 1034 - SU 1035
Photogrammetric capture of stratigraphic units 1034 - 1035 Source: Objaverse 1.0 / Sketchfab
TARP 2019: SU 2095, SU 2096, SU 2097
Photogrammetric capture of stratigraphic units 2095 - 2097 Source: Objaverse 1.0 / Sketchfab
TARP 2019: SU 1076 - SU 1078
Photogrammetric capture of stratigraphic units 1076 - 1078 Source: Objaverse 1.0 / Sketchfab
TARP 2019: SU 2040
Photogrammetric capture of stratigraphic unit 2040. Source: Objaverse 1.0 / Sketchfab
TARP 2019: SU 1079 - SU 1082
Photogrammetric capture of stratigraphic units 1079 - 1082. Source: Objaverse 1.0 / Sketchfab
TARP 2019: SA 2000 Close-out
Photogrammetric capture of SA 2000, Close out Source: Objaverse 1.0 / Sketchfab
TARP 2019: SU 2085
Photogrammetric capture of stratigraphic unit 2085 Source: Objaverse 1.0 / Sketchfab
TARP 2019: SU 1072 - SU 1075
Photogrammetric capture of stratigraphic units 1072 - 1075 Source: Objaverse 1.0 / Sketchfab
TARP 2019: SU 2012, SU 2013
Photogrammetric capture of stratigraphic units 2012-13 Source: Objaverse 1.0 / Sketchfab
Sea ice bulk density estimates during the MOSAiC freezing season from October 2019 to April 2020
<h2><strong><em>MOSAiC: the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition.</em></strong></h2> <p>Assuming hydrostatic equilibrium, we integrated and adjusted sea ice thickness and snow depth data from an IMB array (comprising 15 buoys), high-resolution along-track freeboard data from airborne laser scanning (ALS) and the Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) measurements, as well as snow bulk density data from snow pits, to estimate the ice bulk density (IBD) within the MOSAiC DN (defined as the area within 50 km of Polarstern) during the MOSAiC freezing season from late October 2019 to late April 2020 (<strong>Regional buoy sites</strong>). Additionally, we also provided core-based IBD data from the MOSAiC Main Coring Sites (MCS), derived using the weighing method (<strong>MCS-FYI </strong>and <strong>MCS-SYI</strong>). Due to the challenges in reconciling spatially non-overlapping observations, we implemented two alternative approaches—<strong>Regional Case 1</strong> and <strong>Regional Case 2</strong>—to further upscale the hydrostatic equilibrium-based IBD retrievals within the MOSAiC DN. </p> <h2><em><strong>Variable Details:</strong></em></h2> <p><em><strong>Note that all density results are in kilograms per cubic metre.</strong></em></p> <blockquote> <p><strong>[Time]: </strong>covering the period from 5 October 2019 to 30 April 2020 in the format yyyyMMdd.</p> <p><strong>[Longitude] & [Latitude]</strong>: characterizing the daily position for the MOSAiC Central Observatory (CO).</p> </blockquote> <p> </p> <blockquote> <p><strong>[Reg_buoy_DN]: </strong>Estimated mean sea ice bulk density at the buoy siteswithin a radius of ~50 km from CO (DN scale).</p> <p><strong>[Reg_buoy_DN_Unc1]: </strong>Uncertainty of <strong>[Reg_buoy_DN]</strong> resulting from the input parameters, calculated using the Gaussian error propagation method.</p> <p><strong>[Reg_buoy_DN_Unc2]: </strong>Uncertainty of <strong>[Reg_buoy_DN]</strong> resulting from the introduced empirical adjustment coefficient, characterised using the mean absolute difference of multiple freeboard estimates.</p> </blockquote> <p> </p> <blockquote> <p><strong>[Reg_buoy_Lsite]: </strong>Estimated mean sea ice bulk density at the buoy sites within a radius of ~25 km from CO (Lsite scale).</p> <p><strong>[Reg_buoy_Lsite_Unc1]: </strong>Uncertainty of <strong>[Reg_buoy_Lsite]</strong> resulting from the input parameters, calculated using the Gaussian error propagation method.</p> <p><strong>[Reg_buoy_Lsite_Unc2]: </strong>Uncertainty of <strong>[Reg_buoy_Lsite]</strong> resulting from the introduced empirical adjustment coefficient, characterized using the mean absolute difference of multiple freeboard estimates.</p> </blockquote> <p> </p> <blockquote> <p><strong>[Reg_buoy_DL]: </strong>Mean value of <strong>[Reg_buoy_DN]</strong> and <strong>[Reg_buoy_Lsite]</strong>, representing regional buoy estimates of IBD within the MOSAiC DN.</p> <p><strong>[Reg_buoy_DL_Unc1]: </strong>Uncertainty of <strong>[Reg_buoy_DL]</strong> resulting from the input parameters, calculated using the Gaussian error propagation method.</p> <p><strong>[Reg_buoy_DL_Unc2]: </strong>Uncertainty of <strong>[Reg_buoy_DL] </strong>resulting from the introduced empirical adjustment coefficient, characterized using the mean absolute difference of multiple freeboard estimates.</p> </blockquote> <p> </p> <blockquote> <p><strong>[Reg_case1_DN]: </strong>Mean IBD value for typical ice conditions at the DN scale, calculated using the integration of multi-source observations.</p> <p><strong>[Reg_case2_DN]: </strong>Mean IBD value for typical ice conditions at the DN scale, calculated using initial values from large-scale observations and trend extrapolation.</p> </blockquote> <p> </p> <blockquote> <p><strong>[Loc_MCS_FYI]: </strong>Local-scale core-based bulk density derived from the main first-year coring sites (MCS-FYI) during MOSAiC.</p> <p><strong>[Loc_MCS_SYI]: </strong>Local-scale core-based bulk density derived from the main second-year coring sites (MCS-SYI) during MOSAiC.</p> <p>The density of these ice cores was measured in a freezing laboratory at an ambient temperature of –15 °C using the hydrostatic weighing method, achieving a relatively low uncertainty of <strong>only 0.2%</strong> (Pustogvar and Kulyakhtin, 2016).</p> <p>Pustogvar, A. and Kulyakhtin, A.: Sea ice density measurements. Methods and uncertainties, Cold Regions Science and Technology, 131, 46-52, https://doi.org/10.1016/j.coldregions.2016.09.001, 2016.</p> </blockquote> <p> </p> <h2><em><strong>Relevant datasets:</strong></em></h2> <p><em><strong>Sea ice mass balance buoys (IMBs): sea ice thickness and snow depth</strong></em></p> <blockquote> <p>SIMBA buoy measurements are available from PANGAEA: https://doi.org/10.1594/PANGAEA.938244.</p> <p>SIMB buoy measurements are available from the Arctic Data Center: https://doi.org/10.18739/A20Z70Z01.</p> <p>Lei, R., Cheng, B., Hoppmann, M., and Zuo, G.: Snow depth and sea ice thickness derived from the measurements of SIMBA buoys deployed in the Arctic Ocean during the Legs 1a, 1, and 3 of the MOSAiC campaign in 2019-2020, PANGAEA [data set], https://doi.org/10.1594/PANGAEA.938244, 2021.</p> <p>Perovich, D., Raphael, I., Moore, R., Clemens-Sewall, D., Polashenski, C., and Planck, C.: Measurements of ice mass balance and temperature from autonomous Seasonal Ice Mass Balance buoys in the Arctic Ocean, 2019-2020, Arctic Data Center [data set], https://doi.org/10.18739/A20Z70Z01, 2022.</p> </blockquote> <p> </p> <p><em><strong>Airborne laser scanning (ALS): sea ice total freeboard (sea ice freeboard + snow depth)</strong></em></p> <blockquote> <p>Airborne laser scanning measurements during MOSAiC are available from PANGAEA: https://doi.org/10.1594/PANGAEA.950896.</p> <p>Hutter, N., Hendricks, S., Jutila, A., Birnbaum, G., von Albedyll, L., Ricker, R., and Haas, C.: Gridded segments of sea-ice or snow surface elevation and freeboard from helicopter-borne laser scanner during the MOSAiC expedition, version 1. PANGAEA [data set], https://doi.org/10.1594/PANGAEA.950339, 2023.</p> </blockquote> <p> </p> <p><em><strong>Ice, Cloud, and land Elevation Satellite-2 (ICESat-2): sea ice total freeboard (sea ice freeboard + snow depth)</strong></em></p> <blockquote> <p>ICESat-2 ATL10 total freeboard data (version 6, latest version) are available from NSIDC: https://doi.org/10.5067/ATLAS/ATL10.006.</p> <p>Kwok, R., Petty, A., Cunningham, G., Markus, T., Hancock, D., Ivanoff, A., Wimert, J., Bagnardi, M., and Kurtz, N.: ATLAS/ICESat-2 L3A Sea Ice Freeboard, Version 6, National Snow and Ice Data Center, Boulder, Colorado, USA [data set], https://doi.org/10.5067/ATLAS/ATL10.006, 2023. </p> </blockquote> <p> </p> <p><em><strong>Snow pits: snow density</strong></em></p> <blockquote> <p>Snow pit data collected during the MOSAiC expedition are available from PANGAEA: https://doi.org/10.1594/PANGAEA.940214.</p> <p>Macfarlane, A. R., Schneebeli, M., Dadic, R., Wagner, D. N., Arndt, S., Clemens-Sewall, D., Hämmerle, S., Hannula, H.-R., Jaggi, M., Kolabutin, N., Krampe, D., Lehning, M., Matero, I., Nicolaus, M., Oggier, M., Pirazzini, R., Polashenski, C., Raphael, I., Regnery, J., Shimanchuck, E., Smith, M. M., and Tavri, A.: Snowpit snow density cutter profiles measured during the MOSAiC expedition, PANGAEA [data set], https://doi.org/10.1594/PANGAEA.940214, 2022.</p> </blockquote> <p> </p> <p><em><strong>Transects: sea ice thickness and snow depth</strong></em></p> <blockquote> <p>Transect data collected during MOSAiC are available from PANGAEA: https://doi.org/10.1594/PANGAEA.937781.</p> <p>Itkin, P., Webster, M., Hendricks, S., Oggier, M., Jaggi, M., Ricker, R., Arndt, S., Divine, D. V., von Albedyll, L., Raphael, I., Rohde, J., and Liston, G. E.: Magnaprobe snow and melt pond depth measurements from the 2019-2020 MOSAiC expedition. PANGAEA [data set], https://doi.org/10.1594/PANGAEA.937781, 2021.</p> </blockquote> <p> </p> <p><em><strong>Ice cores: sea ice density</strong></em></p> <blockquote> <p>Ice core data collected from the MOSAiC Main Coring Sites are available from PANGAEA: https://doi.org/10.1594/PANGAEA.956732 (MCS-FYI) and https://doi.org/10.1594/PANGAEA.959830 (MCS-SYI).</p> <p>Oggier, M., Salganik, E., Whitmore, L., Fong, A. A., Hoppe, C. J. M., Rember, R., Høyland, K. V., Divine, D. V., Gradinger, R., Fons, S. W., Abrahamsson, K., Aguilar-Islas, A. M., Angelopoulos, M., Arndt, S., Balmonte, J. P., Bozzato, D., Bowman, J. S., Castellani, G., Chamberlain, E., Creamean, J., D'Angelo, A., Damm, E., Dumitrascu, A., Eggers, S. L., Gardner, J., Grosfeld, L., Haapala, J., Immerz, A., Kolabutin, N., Lange, B. A., Lei, R., Marsay, C. M., Maus, S., Müller, O., Olsen, L. M., Nuibom, A., Ren, J., Rinke, A., Sheikin, I., Shimanchuk, E., Snoeijs-Leijonmalm, P., Spahic, S., Stefels, J., Torres-Valdés, S., Torstensson, A., Ulfsbo, A., Verdugo, J., Vortkamp, M., Wang, L., Webster, M., Wischnewski, L., and Granskog, M. A.: First-year sea-ice salinity, temperature, density, oxygen and hydrogen isotope composition from the main coring site (MCS-FYI) during MOSAiC legs 1 to 4 in 2019/2020. PANGAEA [data set], https://doi.org/10.1594/PANGAEA.956732, 2023.</p> <p>Oggier, M., Salganik, E., Whitmore, L., Fong, A. A., Hoppe, C. J. M., Rember, R., Høyland, K. V., Gradinger, R., Divine, D. V., Fons, S. W., Abrahamsson, K., Aguilar-Islas, A. M., Angelopoulos, M., Arndt, S., Balmonte, J. P., Bozzato, D., Bowman, J. S., Castellani, G., Chamberlain, E., Creamean, J., D'Angelo, A., Damm, E., Dumitrascu, A., Eggers, L., Gardner, J., Grosfeld, L., Haapala, J., Immerz, A., Kolabutin, N., Lange, B. A., Lei, R., Marsay, C. M., Maus, S., Olsen, L. M., Müller, O., Nuibom, A., Ren, J., Rinke, A., Sheikin, I., Shimanchuk, E., Snoeijs-Leijonmalm, P., Spahic, S., Stefels, J., Torres-Valdés, S., Torstensson, A., Ulfsbo, A., Verdugo, J., Vortkamp, M., Wang, L., Webster, M., Wischnewski, L., and Granskog, M. A.: Second-year sea-ice salinity, temperature, density, oxygen and hydrogen isotope composition from the main coring site (MCS-SYI) during MOSAiC legs 1 to 4 in 2019/2020. PANGAEA [data set], https://doi.org/10.1594/PANGAEA.959830, 2023.</p> </blockquote> <p> </p>
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Allen Brain Atlas
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International Brain Laboratory public data
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OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.