In May 2013, the Grand Canyon Monitoring and Research Center (GCMRC) of the U.S. Geological Survey’s (USGS) Southwest Biological Science Center (SBSC) acquired airborne multispectral high resolution data for the Colorado River in Grand Canyon in Arizona, USA. The imagery data consist of four bands (blue, green, red and near infrared) with a ground resolution of 20 centimeters (cm). These data are available to the public as 16-bit geotiff files. They are projected in the State Plane (SP) map projection using the central Arizona zone (202) and the North American Datum of 1983 (NAD83). The assessed accuracy for these data is based on 91 Ground Control Points (GCPs), and is reported at 95% confidence as 0.64 meters (m) and a Root Mean Square Error (RMSE) of 0.36m. The airborne data acquisition was conducted under contract by Fugro Earthdata Inc. using two fixed wing aircraft from May 25th to 30th, 2013 at altitudes between 2440 meters to 3350 meters above mean sea level. The data delivered by Fugro Earthdata Inc. were checked for smear, shadow extent and water clarity as described for previous image acquisitions in Davis (2012). We then produced a corridor-wide mosaic using the best possible tiles with the least amount of smear, the smallest shadow extent, and clearest, most glint-free water possible. During the mosaic process adjacent tiles sometimes had to be spectrally adjusted to account for differences in date, time, sun angle, weather, and environment. We used the same method as described in Davis (2012) for the spectral adjustment. A horizontal accuracy assessment was completed by Fugro Earthdata Inc. using 188 GCPs provided by GCMRC. The GCPs were marked during the image acquisition with 1m2 diagonally alternated black and white plastic panels centered on control points throughout the river corridor in the GCMRC survey control network (Hazel and others, 2008). The Root Mean Square Error (RMSE) accuracy reported by Fugro Earthdata Inc. is 0.17m Easting and 0.15m Northing, or better, depending on the acquisition zone. The 16-bit image data are stored as four band images in embedded geotiff format, which can be read and used by most geographic information system (GIS) and image-processing software. The TIFF world files (tfw) are provided, however they are not needed for many software to read an embedded geotiff image. The image files are projected in the State Plane (SP) 2011, map projection using the central Arizona zone (202) and the North American Datum of 1983 (NAD83). A complete detailed description of the methods can be found in the associated USGS Data Series 1027 for these data, https://pubs.er.usgs.gov/publication/ds1027.

MOSAiC: the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition.

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 (Regional buoy sites). Additionally, we also provided core-based IBD data from the MOSAiC Main Coring Sites (MCS), derived using the weighing method (MCS-FYI and MCS-SYI). Due to the challenges in reconciling spatially non-overlapping observations, we implemented two alternative approaches—Regional Case 1 and Regional Case 2—to further upscale the hydrostatic equilibrium-based IBD retrievals within the MOSAiC DN.

Variable Details:

Note that all density results are in kilograms per cubic metre.

[Time]: covering the period from 5 October 2019 to 30 April 2020 in the format yyyyMMdd.

[Longitude] & [Latitude]: characterizing the daily position for the MOSAiC Central Observatory (CO).

[Reg_buoy_DN]: Estimated mean sea ice bulk density at the buoy siteswithin a radius of ~50 km from CO (DN scale).

[Reg_buoy_DN_Unc1]: Uncertainty of [Reg_buoy_DN] resulting from the input parameters, calculated using the Gaussian error propagation method

[Reg_buoy_DN_Unc2]: Uncertainty of [Reg_buoy_DN] resulting from the introduced empirical adjustment coefficient, characterised using the mean absolute difference of multiple freeboard estimates.

[Reg_buoy_Lsite]: Estimated mean sea ice bulk density at the buoy sites within a radius of ~25 km from CO (Lsite scale).

[Reg_buoy_Lsite_Unc1]: Uncertainty of [Reg_buoy_Lsite] resulting from the input parameters, calculated using the Gaussian error propagation method

[Reg_buoy_Lsite_Unc2]: Uncertainty of [Reg_buoy_Lsite] resulting from the introduced empirical adjustment coefficient, characterized using the mean absolute difference of multiple freeboard estimates.

[Reg_buoy_DL]: Mean value of [Reg_buoy_DN] and [Reg_buoy_Lsite], representing regional buoy estimates of IBD within the MOSAiC DN.

[Reg_buoy_DL_Unc1]: Uncertainty of [Reg_buoy_DL] resulting from the input parameters, calculated using the Gaussian error propagation method

[Reg_buoy_DL_Unc2]: Uncertainty of [Reg_buoy_DL] resulting from the introduced empirical adjustment coefficient, characterized using the mean absolute difference of multiple freeboard estimates.

[Reg_case1_DN]: Mean IBD value for typical ice conditions at the DN scale, calculated using initial values from large-scale observations and trend extrapolation.

[Reg_case2_DN]: Mean IBD value for typical ice conditions at the DN scale, calculated using the integration of multi-source observations.

[Loc_MCS_FYI]: Local-scale core-based bulk density derived from the main first-year coring sites (MCS-FYI) during MOSAiC.

[Loc_MCS_SYI]: Local-scale core-based bulk density derived from the main second-year coring sites (MCS-SYI) during MOSAiC.

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 only 0.2% (Pustogvar and Kulyakhtin, 2016).

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.

Relevant datasets:

Sea ice mass balance buoys (IMBs): sea ice thickness and snow depth

SIMBA buoy measurements are available from PANGAEA: https://doi.org/10.1594/PANGAEA.938244

SIMB buoy measurements are available from the Arctic Data Center: https://doi.org/10.18739/A20Z70Z01

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.

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.

Airborne laser scanning (ALS): sea ice total freeboard (sea ice freeboard + snow depth)

Airborne laser scanning measurements during MOSAiC are available from PANGAEA: https://doi.org/10.1594/PANGAEA.950896.

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.

Ice, Cloud, and land Elevation Satellite-2 (ICESat-2): sea ice total freeboard (sea ice freeboard + snow depth)

ICESat-2 ATL10 total freeboard data (version 6, latest version) are available from NSIDC: https://doi.org/10.5067/ATLAS/ATL10.006.

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. 

Snow pits: snow density

Snow pit data collected during the MOSAiC expedition are available from PANGAEA: https://doi.org/10.1594/PANGAEA.940214.

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.

Transects: sea ice thickness and snow depth

Transect data collected during MOSAiC are available from PANGAEA: https://doi.org/10.1594/PANGAEA.937781.

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.

Ice cores: sea ice density

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).

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.

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.,