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The 3D dust complexity maps used in the main result of Section 4 <a href="https://arxiv.org/abs/2404.11009">"Imprints of the Local Bubble and Dust Complexity on Polarized Dust Emission," Halal et al. 2024</a>. Use of these data must cite that paper. We provide 12 maps, corresponding to the 12 posterior sample 3D dust extinction maps of <a href="https://www.aanda.org/articles/aa/full_html/2024/05/aa47628-23/aa47628-23.html">Edenhofer et al. 2023</a>, which extend radially out to 1.25 kpc. The maps we provide are in Galactic coordinates and are only defined over the masks described in <a href="https://arxiv.org/abs/2404.11009">Halal et al. 2024</a>.
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Halal et al. 2023 3D HI-based Stokes Parameter Maps
The HI-based Stokes parameter maps used in (https://arxiv.org/abs/2306.10107) Filamentary Dust Polarization and the Morphology of HI Structures, Halal et al. 2023. Use of these data must cite that paper and (https://ui.adsabs.harvard.edu/abs/2019ApJ...887..136C/abstract) Clark & Hensley 2019. There are four sets of data cubes: one at Nside=1024 based on the 4' GALFA-HI data computed using the Spherical RHT algorithm, one at Nside=2048 based on the 4' GALFA-HI data smoothed to 7' computed using the Hessian algorithm, and two at Nside=1024 based on the 16.2' HI4PI data (one computed using the Spherical RHT algorithm and the other using the Hessian algorithm). A map based on the Hessian algorithm and the 16.2' HI4PI data, integrated over the velocity range -13 km/s to 16 km/s (Section 4.1 in Halal et al. 2023), is also available. The provided data cubes can be used to produce integrated maps over any velocity range desired. <br/><br/> These maps are given in units of K km/s and follow the Galactic IAU polarization convention. Multiply U by -1 to obtain maps corresponding to the COSMO convention as those provided by Planck. Multiply both Q and U by -1 to obtain maps corresponding to the magnetic field orientation in the IAU convention. <br/><br/> Please see (https://github.com/seclark/ClarkHensley2019) for code that demonstrates the use of data of the same format. The velocity binning of this data follows that of <a href="https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/P41KDE">Clark & Hensley 2019</a> and can be found <a href="https://github.com/seclark/ClarkHensley2019/tree/master/data">here</a>.
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- Award ID(s):
- 2106607
- PAR ID:
- 10562788
- Publisher / Repository:
- Harvard Dataverse
- Date Published:
- Subject(s) / Keyword(s):
- Astronomy Astrophysics Dust Polarization
- Format(s):
- Medium: X Size: 2474900413; 343115439; 1440378273; 18543664; 2063599616; 2598113379; 18599423; 1458937575; 2517324464; 343756902; 301996800 Other: application/x-hdf5; application/x-hdf5; application/x-hdf5; application/x-hdf5; application/x-hdf5; application/x-hdf5; application/x-hdf5; application/x-hdf5; application/x-hdf5; application/x-hdf5; application/fits
- Size(s):
- 2474900413 343115439 1440378273 18543664 2063599616 2598113379 18599423 1458937575 2517324464 343756902 301996800
- Right(s):
- Creative Commons Zero v1.0 Universal
- Sponsoring Org:
- National Science Foundation
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{"Abstract":["The intended use of this archive is to facilitate meta-analysis of the Data Observation Network for Earth (DataONE, [1]). <\/p>\n\nDataONE is a distributed infrastructure that provides information about earth observation data. This dataset was derived from the DataONE network using Preston [2] between 17 October 2018 and 6 November 2018, resolving 335,213 urls at an average retrieval rate of about 5 seconds per url, or 720 files per hour, resulting in a data gzip compressed tar archive of 837.3 MB . <\/p>\n\nThe archive associates 325,757 unique metadata urls [3] to 202,063 unique ecological metadata files [4]. Also, the DataONE search index was captured to establish provenance of how the dataset descriptors were found and acquired. During the creation of the snapshot (or crawl), 15,389 urls [5], or 4.7% of urls, did not successfully resolve. <\/p>\n\nTo facilitate discovery, the record of the Preston snapshot crawl is included in the preston-ls-* files . There files are derived from the rdf/nquad file with hash://sha256/8c67e0741d1c90db54740e08d2e39d91dfd73566ea69c1f2da0d9ab9780a9a9f . This file can also be found in the data.tar.gz at data/8c/67/e0/8c67e0741d1c90db54740e08d2e39d91dfd73566ea69c1f2da0d9ab9780a9a9f/data . For more information about concepts and format, please see [2]. <\/p>\n\nTo extract all EML files from the included Preston archive, first extract the hashes assocated with EML files using:<\/p>\n\ncat preston-ls.tsv.gz | gunzip | grep "Version" | grep -v "deeplinker" | grep -v "query/solr" | cut -f1,3 | tr '\\t' '\\n' | grep "hash://" | sort | uniq > eml-hashes.txt<\/p>\n\nextract data.tar.gz using:<\/p>\n\n~/preston-archive$$ tar xzf data.tar.gz <\/p>\n\nthen use Preston to extract each hash using something like:<\/p>\n\n~/preston-archive$$ preston get hash://sha256/00002d0fc9e35a9194da7dd3d8ce25eddee40740533f5af2397d6708542b9baa\n<eml:eml xmlns:eml="eml://ecoinformatics.org/eml-2.1.1" xmlns:xs="http://www.w3.org/2001/XMLSchema" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:stmml="http://www.xml-cml.org/schema/stmml_1.1" packageId="doi:10.18739/A24P9Q" system="https://arcticdata.io" scope="system" xsi:schemaLocation="eml://ecoinformatics.org/eml-2.1.1 ~/development/eml/eml.xsd">\n <dataset>\n <alternateIdentifier>urn:x-wmo:md:org.aoncadis.www::d76bc3b5-7b19-11e4-8526-00c0f03d5b7c</alternateIdentifier>\n <alternateIdentifier>d76bc3b5-7b19-11e4-8526-00c0f03d5b7c</alternateIdentifier>\n <title>Airglow Image Data 2011 4 of 5</title>\n...<\/p>\n\nAlternatively, without using Preston, you can extract the data using the naming convention:<\/p>\n\ndata/[x]/[y]/[z]/[hash]/data<\/p>\n\nwhere x is the first 2 characters of the hash, y the second 2 characters, z the third 2 characters, and hash the full sha256 content hash of the EML file.<\/p>\n\nFor example, the hash hash://sha256/00002d0fc9e35a9194da7dd3d8ce25eddee40740533f5af2397d6708542b9baa can be found in the file: data/00/00/2d/00002d0fc9e35a9194da7dd3d8ce25eddee40740533f5af2397d6708542b9baa/data . For more information, see [2].<\/p>\n\nThe intended use of this archive is to facilitate meta-analysis of the DataONE dataset network. <\/p>\n\n[1] DataONE, https://www.dataone.org\n[2] https://preston.guoda.bio, https://doi.org/10.5281/zenodo.1410543 . DataONE was crawled via Preston with "preston update -u https://dataone.org".\n[3] cat preston-ls.tsv.gz | gunzip | grep "Version" | grep -v "deeplinker" | grep -v "query/solr" | cut -f1,3 | tr '\\t' '\\n' | grep -v "hash://" | sort | uniq | wc -l\n[4] cat preston-ls.tsv.gz | gunzip | grep "Version" | grep -v "deeplinker" | grep -v "query/solr" | cut -f1,3 | tr '\\t' '\\n' | grep "hash://" | sort | uniq | wc -l\n[5] cat preston-ls.tsv.gz | gunzip | grep "Version" | grep "deeplinker" | grep -v "query/solr" | cut -f1,3 | tr '\\t' '\\n' | grep -v "hash://" | sort | uniq | wc -l<\/p>\n\nThis work is funded in part by grant NSF OAC 1839201 from the National Science Foundation.<\/p>"]}more » « less
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<p>NSF COLDEX performed two airborne campaigns from South Pole Station over the Southern Flank of Dome A and 2022-23 and 2023-24, searching for a potential site of a continuous ice core that could sample the mid-Pleistocene transition. Ice thickness data extracted from the MARFA radar system has allow for a new understanding of this region.</p> <p>Here we generate crustal scale maps of ice thickness, bed elevation, specularity content, subglacial RMS deviation and fractional basal ice thickness with 1 km sampling, and 10 km resolution. We include both masked and unmasked grids.</p> <p> The projection is in the SCAR standard ESPG:3031 polar stereographic projection with true scale at 71˚S.</p> <p>These geotiffs were generated using performed using GMT6.5 (<a href="https://doi.org/10.1029/2019GC008515">Wessel et al., 2019</a>) using the pygmt interface, by binning the raw data to 2.5 km cells, and using the <a href="https://github.com/sakov/nn-c"> nnbathy </a> program to apply natural neighbor interpolation to 1 km sampling. A 10 km Gaussian filter - representing typical lines spacings - was applied and then a mask was applied for all locations where the nearest data point was further than 8 km. </p> Ice thickness, bed elevation and RMS deviation @ 400 m length scale (<a href="http://dx.doi.org/10.1029/2000JE001429">roughness</a>) data includes the following datasets: <ul> <li> UTIG/CRESIS <a href="https://doi.org/10.18738/T8/J38CO5">NSF COLDEX Airborne MARFA data</a></li> <li> British Antarctic Survey <a href="https://doi.org/10.5285/0f6f5a45-d8af-4511-a264-b0b35ee34af6">AGAP-North</a></li> <li> LDEO <a href="https://doi.org/10.1594/IEDA/317765"> AGAP-South </a></li> <li> British Antarctic Survey <a href="https://doi.org/10.5270/esa-8ffoo3e">Polargap</a></li> <li> UTIG Support Office for Airborne Research <a href="https://doi.org/10.15784/601588">Pensacola-Pole Transect (PPT) </a></li> <li> NASA/CReSIS <a href="https://doi.org/10.5067/GDQ0CUCVTE2Q"> 2016 and 2018 Operation Ice Bridge </a> </li> <li> ICECAP/PRIC <a href="https://doi.org/10.15784/601437"> SPICECAP Titan Dome Survey </a> </ul> <p>Specularity content (<a href="https://doi.org/10.1109/LGRS.2014.2337878">Schroeder et al. 2014</a>) is compiled from <a href="https://doi.org/10.18738/T8/KHUT1U"> Young et al. 2025a </a> and <a href="https://doi.org/10.18738/T8/6T5JS6"> Young et al. 2025b</a>.</p> <p>Basal ice fractional thickness is complied from manual interpretation by Vega Gonzàlez, Yan and Singh. </p> <p>Code to generated these grids can be found at <a href="https://github.com/smudog/COLDEX_dichotomy_paper_2025"> at github.com </a></p>more » « less
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<p><b> Introduction </b> <br> The National Science Foundations Center for Oldest Ice Exploration (<a href="https://www.coldex.org">NSF COLDEX</a>) is a Science and Technology Center working to extend the record of atmospheric gases, temperature and ice sheet history to greater than 1 million years. As part of this effort, NSF COLDEX has been searching for a site for a continuous ice core extending through the mid-Pleistocene transition. Two seasons of airborne survey were conducted from South Pole Station across the southern flank of Dome A. </p> <p><b> 2023-2024 Field Season </b> <br> In the 2023-2024 field season (CXA2), and using a BT-67 Basler, NSF COLDEX conducted 17 flights from South Pole Station toward the southern flank of Dome C. Three test flights were conducted from McMurdo Station. Instrumentation included the <a href="https://doi.org/10.18738/T8/J38CO5">60 MHz MARFA ice penetrating radar </a> from the University of Texas Institute for Geophysics, a <a href="https://doi.org/10.1109/IGARSS53475.2024.10640448">UHF ice penetrating radar </a> from the Center for Remote Sensing and Integrated Systems; an GT-2 Gravimeter, and LD-90 laser altimeter and an G-823 Magnetometer. </p> <p><b> Basal specularity content </b> <br> These basal specularity content were derived from comparing 1D and 2D focused MARFA data (<a href="http://doi.org/10.1109/TGRS.2007.897416">Peters et al., 2007</a>). By comparing bed echo strengths for different focusing apertures, and accounting for the ranges and angles involved, we can derive the "specularity content" of the bed echo, a proxy for small scale bed roughness and a good indicator for subglacial water pressure in regions of distributed subglacial water (<a href="https://doi.org/10.1109/LGRS.2014.2337878">Schroeder et al., 2014, IEEE GRSL </a>, <a href="https://doi.org/10.1016/j.epsl.2019.115961">Dow et al., 2019, EPSL </a>) and smooth deforming bed material (<a href="http://doi.org/10.1002/2014GL061645">Schroeder et al., 2014, GRL</a>, <a href="http://dx.doi/org/10.1098/rsta.2014.0297">Young et al., 2016, PTRS</a>. Specularity data are inherently noisy, so these products have been smoothed with a 1 km filter.</p>more » « less
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<p><b> Introduction </b> <br> The National Science Foundations Center for Oldest Ice Exploration (<a href="https://www.coldex.org">NSF COLDEX</a>) is a Science and Technology Center working to extend the record of atmospheric gases, temperature and ice sheet history to greater than 1 million years. As part of this effort, NSF COLDEX has been searching for a site for a continuous ice core extending through the mid-Pleistocene transition. Two seasons of airborne survey were conducted from South Pole Station across the southern flank of Dome A. </p> <p><b> 2022-2023 Field Season </b> <br> In the 2022-20223 field season (CXA1), and using a BT-67 Basler, NSF COLDEX conducted 13 full flights and one weather abort from South Pole Station toward the southern flank of Dome C; as well as 1 survey flight toward Hercules Dome in support of the Hercules Dome Drilling project. Three test flights were conducted from McMurdo Station. Instrumentation included the <a href="https://doi.org/10.18738/T8/J38CO5">60 MHz MARFA ice penetrating radar </a> from the University of Texas Institute for Geophysics, a <a href="https://doi.org/10.1109/IGARSS53475.2024.10640448">UHF ice penetrating radar </a> from the Center for Remote Sensing and Integrated Systems; an GT-2 Gravimeter, and LD-90 laser altimeter and an G-823 Magnetometer. </p> <p><b> Basal specularity content </b> <br> These basal specularity content were derived from comparing 1D and 2D focused MARFA data (<a href="http://doi.org/10.1109/TGRS.2007.897416">Peters et al., 2007</a>). By comparing bed echo strengths for different focusing apertures, and accounting for the ranges and angles involved, we can derive the "specularity content" of the bed echo, a proxy for small scale bed roughness and a good indicator for subglacial water pressure in regions of distributed subglacial water (<a href="https://doi.org/10.1109/LGRS.2014.2337878">Schroeder et al., 2014, IEEE GRSL </a>, <a href="https://doi.org/10.1016/j.epsl.2019.115961">Dow et al., 2019, EPSL </a>) and smooth deforming bed material (<a href="http://doi.org/10.1002/2014GL061645">Schroeder et al., 2014, GRL</a>, <a href="http://dx.doi/org/10.1098/rsta.2014.0297">Young et al., 2016, PTRS</a>. Specularity data are inherently noisy, so these products have been smoothed with a 1 km filter.</p>more » « less
