High-Resolution Repeat Topography of Drifting Ice Floes in the Arctic Ocean from Terrestrial Laser Scanning Collected on the Multidisciplinary drifting Observatory for the Study of Arctic Climate Expedition

Data are available for download at: https://arcticdata.io/data/10.18739/A2GH9BB4N/ Many processes involving the fluxes of mass, energy, and momentum in Arctic sea ice impact and are impacted by the snow and ice topography. We conducted 42 days of measuring the snow and ice topography on approximatel...

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Bibliographic Details
Main Authors: David Clemens-Sewall, Chris Polashenski, Ian Raphael, Don Perovich, Steven Fons, Polona Itkin, Matthias Jaggi, Arttu Jutila, Amy Macfarlane, Ilkka Matero, Marc Oggier, David Wagner, Ronald Visser, Thomas Olufson, Martin Radenz, Carl Schönning, Jesper Hansen, Monica Votvik, Eric Brossier, Saga Svavarsdottir
Format: Dataset
Language:unknown
Published: Arctic Data Center 2022
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Online Access:https://search.dataone.org/view/urn:uuid:81be50e1-563d-4c4f-b5a2-24f8afd4339b
Description
Summary:Data are available for download at: https://arcticdata.io/data/10.18739/A2GH9BB4N/ Many processes involving the fluxes of mass, energy, and momentum in Arctic sea ice impact and are impacted by the snow and ice topography. We conducted 42 days of measuring the snow and ice topography on approximately a 0.5 km squared drifting parcel of Arctic sea ice from 18 October 2019 to 9 May 2020 via Terrestrial Laser Scanning (TLS) on the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition. We have aligned the TLS data into an ice-fixed, lagrangian reference frame such that topographic changes (e.g. snow accumulation) can be observed on some ice floes for time periods up to six months. Using in-situ measurements, we have validated the vertical accuracy of the alignment to within a 95% confidence interval of plus or minus 0.011 m. These data can be used to investigate snow accumulation and redistribution, ice dynamics, surface roughness, and they can provide invaluable context for many other co-located measurements. These measurements were made as part of the snow and ice team work at MOSAiC. For an overview of all snow and ice team work please see: https://doi.org/10.1525/elementa.2021.000046. Additionally, a data descriptor paper providing additional details, figures, and tables related to this dataset will be published following publication of this dataset. This dataset supersedes https://doi.org/10.18739/A25717P9Q, https://doi.org/10.18739/A2901ZH4K, and https://doi.org/10.18739/A2DR2P98D. This dataset contains all information in those prior datasets and has superior alignment quality. These data are stored within a directory tree (see Methods section below). The following wget command will download the entire data archive, which is 350 GB: wget -r -np -nH --cut-dirs=3 -R '\?C=' -R robots.txt -R 'index.html*' https://arcticdata.io/data/10.18739/A26688K9D/ To download just a subdirectory (e.g., the 'Snow1' scan area, or an individual project): go to https://arcticdata.io/data/10.18739/A2GH9BB4N/, navigate to the desired subdirectory, and replace the url in the wget command with the url of the desired subdirectory. A processing library ('pydar') for working with these data is available at: https://zenodo.org/records/10152870