More Like this

1. Radar Classification of the Antarctic Ice-Bed Interface: Version 2

   https://doi.org/10.18738/t8/c8ie7c  

   Young, Duncan; Young, Duncan (January 2025, Texas Data Repository)

   {"Abstract":["This classified_bed data product represents the radar bed classification shown in <a href="https://doi.org/10.1098/rsta.2014.0297">Young et al., 2016</a>. Values of 0 represent specularity content below 20%; values of 3.3 represent specularity content above 20% and energy 1 microsecond below the bed 15 dB lower than the bed echo, and values of 6.7 represent specularity content above 20% and energy 1 microsecond below the bed 15 dB within than the bed echo. Grids for specularity content and post bed echo are also available. Data is available as COARDS-compliant netCDF-4/HDF5 grids (.grd) and GeoTiffs (.tiff), both in EPSG 3031 (Antarctic Polar Stereographic) projection.\n<p>\n<p>\nData were gridded using <a href="https://docs.generic-mapping-tools.org/6.1/gmt.html"> GMT6.1</a> and the <a href="https://github.com/sakov/nn-c">nnbathy</a> natural neighbor interpolator. Cell size was 1 km, gaussian filter distance was 5 km, and mask radius was 2 km.\n<p>\nBrowse images, with Bedmap3 (Pritchard et al., 2025) surface elevation contours and MEASURES phase derived surface velocities (Mouginot et al. 2019) are available for each dataset.\n\n<p>\n<p>\nAn interpretation of the values in the classified_bed product is that low values are rough bed, intermediate values are isotropic wet bed, and high values are anisotropic wet bed.\n\nVersion 1 includes data from the 2016 paper, including AGASEA over Thwaites Glacier (Holt et al., 2006), ATRS over West Antarctica (Peters et al., 2005), GIMBLE over Marie Byrd Land (Young et al, 2013) and parts of ICECAP over Wilkes Subglacial Basin, Dome C, Highland B and Totten Glacier. (Young et al, 2011, Young et al., 2016). We expect updates to the coverage as part of work funded by the Arête Glaciers Initiative.\n\n<p>\n<b>References</b>\n<br>\nHolt, J. W., Blankenship, D. D., Morse, D. L., Young, D. A., Peters, M. E., Kempf, S. D., Richter, T. G., Vaughan, D. G., and Corr, H., New boundary conditions for the West Antarctic ice sheet: subglacial topography of the Thwaites and Smith Glacier catchments, 2006, Geophysical Research Letters, 33 (L09502), pp., https://doi.org/10.1029/2005GL025561\n<br>\nMouginot, J., Rignot, E., and Scheuchl, B., Continent-wide, interferometric SAR phase, mapping of Antarctic ice velocity, 2019, Geophysical Research Letters, 46(16), pp.9710-9718, https://doi.org/10.1029/2019GL083826\n<br>\nPeters, M. E., Blankenship, D. D., and Morse, D. L., Analysis techniques for coherent airborne radar sounding: Application to West Antarctic ice streams, 2005 ,Journal of Geophysical Research, 110(B06303), pp.,https://doi.org/10.1029/2004JB003222\n<br>\nPritchard, H. D., and others.,Bedmap3 updated ice bed, surface and thickness gridded datasets for Antarctica,2025,Scientific Data,12(1), pp.414,https://doi.org/10.1038/s41597-025-04672-y\n<br>\nYoung, D. A., D. D. Blankenship, J. S. Greenbaum, E. Quartini, G. L. Muldoon, F. Habbal, L. E. Lindzey, C. A. Greene, E. M. Powell, G. C. Ng, T. G. Richter, G. Echeverry, and S. Kempf, 2024, Geophysical Investigations of Marie Byrd Land Lithospheric Evolution (GIMBLE) Airborne VHF Radar Transects: 2012/2013 and 2014/2015, https://doi.org/10.18738/T8/BMXUHX, Texas Data Repository\n<br>\nYoung, D. A., Wright, A. P., Roberts, J. L., Warner, R. C., Young, N. W., Greenbaum, J. S., Schroeder, D. M., Holt, J. W., Sugden, D. E., Blankenship, D. D., van Ommen, T. D., and Siegert, M. J.,A dynamic early East Antarctic Ice Sheet suggested by ice covered fjord landscapes, 2011, Nature, 474, pp.72-75, https://doi.org/10.1038/nature10114\n<br>\nYoung, D. A., Schroeder, D. M., Blankenship, D. D., Kempf, S. D., and Quartini, E.,The distribution of basal water between Antarctic subglacial lakes from radar sounding,2016,Philosophical Transactions of the Royal Society A, 374 (20140297), pp.1-21, https://doi.org/10.1098/rsta.2014.0297\n\n<p>\n<b>Change Log</b>\n<br>\nChanges from V1: changes to gridding parameters to more closely match the figures from Young 2016; updated metadata gridding description"]} 

   more » « less
2. Modèle Atmosphérique Régional (MAR) version 3.11 regional climate model output, 1979-2019, Greenland domain, 10 kilometer (km) horizontal resolution

   https://doi.org/10.18739/A28G8FJ7F  

   Fettweis, Xavier (January 2022, NSF Arctic Data Center)

   Modèle Atmosphérique Régional (MAR) is a regional climate model that is fully coupled to a one-dimensional surface-atmosphere energy and mass transfer scheme, SISVAT (Soil Ice Snow Vegetation Atmosphere Transfer) (Fettweis et al., 2005, 2020; Lefebre et al., 2005). SISVAT employs a multilayered snowpack model, CROCUS, that simulates meltwater production, percolation, and refreeze (Brun et al., 1989), while also accounting for changes in albedo due to snow metamorphism (Brun et al., 1992). MAR has been extensively verified over the Greenland Ice Sheet and is therefore particularly well suited for analyses of Greenland ice sheet surface mass balance (Fettweis et al., 2011; Fettweis et al., 2020; Lefebre et al. 2005; Mattingly et al. 2020). Brun, E., Martin, E., Simon, V., Gendre, C., and Coléou, C. (1989). An energy and mass model of snow cover suitable for operational avalanche forecasting. Journal of Glaciology, 35, 333. https://doi.org/10.1017/S0022143000009254 Brun, E., David, P., Sudul, M., and Brunot, G. (1992). A numerical model to simulate snow-cover stratigraphy for operational avalanche forecasting. Journal of Glaciology, 38(128), 13–22. https://doi.org/10.3189/S0022143000009552 Fettweis, X., Gallée, H., Lefebre, F., and van Ypersele, J.-P. (2005). Greenland surface mass balance simulated by a regional climate model and comparison with satellite-derived data in 1990–1991. Climate Dynamics, 24(6), 623–640. https://doi.org/10.1007/s00382-005-0010-y Fettweis, X., Tedesco, M., van den Broeke, M., and Ettema, J. (2011). Melting trends over the Greenland ice sheet (1958–2009) from spaceborne microwave data and regional climate models. The Cryosphere, 5(2), 359–375. https://doi.org/10.5194/tc-5-359-2011 Fettweis, X., Hofer, S., Krebs-Kanzow, U., Amory, C., Aoki, T., Berends, C. J., et al. (2020). GrSMBMIP: intercomparison of the modelled 1980–2012 surface mass balance over the Greenland Ice Sheet. The Cryosphere, 14(11), 3935–3958. https://doi.org/10.5194/tc-14-3935-2020 Lefebre, F., Fettweis, X., Gallée, H., Van Ypersele, J.-P., Marbaix, P., Greuell, W., and Calanca, P. (2005). Evaluation of a high-resolution regional climate simulation over Greenland. Climate Dynamics, 25(1), 99–116. https://doi.org/10.1007/s00382-005-0005-8 Mattingly, K. S., Mote, T. L., Fettweis, X., van As, D., Van Tricht, K., Lhermitte, S., et al. (2020). Strong summer atmospheric rivers trigger Greenland ice sheet melt through spatially varying surface energy balance and cloud regimes. Journal of Climate, 33(16), 6809–6832. https://doi.org/10.1175/JCLI-D-19-0835.1 

   more » « less
3. NSF COLDEX 2023-24 Level 2 Basal Specularity Content Profiles

   https://doi.org/10.18738/T8/KHUT1U  

   Young, Duncan; Kerr, Megan E; Singh, Shivangini; Yan, Shuai; Kempf, Scott D; Ng, Gregory; Blankenship, Donald D; Young, Duncan (January 2025, Texas Data Repository)

   <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
4. Elemental concentration and Pb isotope ratio data for the Begguya Summit Plateau ice cores, Begguya (Mt. Hunter), Alaska from 800 to 2022 CE.

   https://doi.org/10.60520/ieda/114284  

   Brooks, Hanna; Kreutz, Karl; Winksi, Dominic; Osterberg, Erich; Handley, Michael; Chalif, Jacob (January 2025, Interdisciplinary Earth Data Alliance (IEDA))

   {"Abstract":["Two parallel surface-to-bedrock ice cores (DEN-13A and DEN-13B) were drilled from the Begguya summit plateau in Denali National Park, Alaska (62.93 N 151.083 W, 3912 m asl; also known as Mount Hunter), during the summer of 2013. The summit of Begguya has a high accumulation rate and low melt rate, making it an ideal site to recover intact paleoclimate records. DEN-13A and DEN-13B, which reach depths of ~210 meters, respectively, cover at least 10,000 years (Fang et al., 2023). Shallow cores were drilled in the summers of 2019 (DEN-19A; 50 meters) and 2022 (DEN-22A; 20 meters) extend the paleoclimate record at this site through 2022. Together, these four ice cores are commonly referred to as the Denali Ice Core record or the Begguya summit plateau ice core record. A robust chronology has been developed using a combination of techniques including annual layer counting, sulfate peaks (volcanics), radiocarbon dating and the 1963 atmospheric nuclear weapons testing horizon (Fang et al., 2023). Here, we report aqueous ICP-MS elemental concentrations and Pb isotope ratio data for the top ~1,200 years (800 to 2022 CE) of the Begguya summit plateau ice core record."],"Other":["Fang, L., Jenk, T. M., Winski, D. A., Kreutz, K. J., Brooks, H. L., Erwin, E., Osterberg, E. C., Campbell, S. W., Wake, C. P., Schwikowski, M, (2023), "Early Holocene ice on the Begguya plateau (Mt. Hunter, Alaska) revealed by ice core 14 C age constraints." The Cryosphere, 17(9):4007-4020; Osterberg, E. C., Winski, D. A., Kreutz, K. J., Wake, C. P., Ferris, D. G., Campbell, S. W., Introne, D. S., Handley, M. J., Birkel, S. D., (2017), "The 1200 year composite ice core record of Aleutian Low intensification." Geophysical Research Letters, 44(14):7447-7454."]} 

   more » « less
5. Stable isotope values of consumers, producers, and organic matter in the Shark River Slough and Taylor Slough, Everglades National Park (FCE LTER), Florida, USA, 2019 – ongoing

   https://doi.org/10.6073/pasta/da36c97eccd5461ba32eecce23a53892  

   Rezek, Ryan (January 2024, Environmental Data Initiative)

   {"Abstract":["Wetland food webs have often been characterized as detrital-based ‘brown’ energy pyramids, whereas the relative role of autotrophic (‘green’) vs. microbial (‘brown’) energy sources falls along a continuum set by physical drivers, as well as autochthonous and allochthonous inputs (Moore et al. 2004; Evans-White & Halvorson 2017) that change with ecosystem development (Schmitz et al. 2006). In the Florida Coastal Everglades (FCE), metabolic imbalances, including the collapse of calcareous periphyton mats, begin with a loss of foundation species primary production and legacy organic matter (Gaiser et al. 2006). This process likely enhances heterotrophic microbial productivity (Schulte 2016) and the supply of detrital energy to consumers by changing bioavailable and recalcitrant carbon supplies (Baggett et al. 2013). A shift from complex periphyton communities to transient planktonic communities under elevated P exposure reduces habitat structure and animal refuges but increases ‘green’ energy supplies and edibility (Trexler et al. 2015; Naja et al. 2017). Multiple sites (n=9) within the FCE were selected to document changes in coastal food webs as a result of eutrophication and increasing hydrologic variability. The project began in 2019 and is currently ongoing.\n \n References:\n Baggett, L. P., Heck, K. L., Frankovich, T. A., Armitage, A. R., & Fourqurean, J. W. (2013). Stoichiometry, growth, and fecundity responses to nutrient enrichment by invertebrate grazers in sub-tropical turtle grass (Thalassia testudinum) meadows. Marine biology, 160, 169-180.\n Evans-White, M. A., and H. M. Halvorson. 2017. Comparing the Ecological Stoichiometry in Green and Brown Food Webs – A Review and Meta-analysis of Freshwater Food Webs. Frontiers in Microbiology 8:1184. \n Gaiser, E. E., Childers, D. L., Jones, R. D., Richards, J. H., Scinto, L. J., & Trexler, J. C. (2006). Periphyton responses to eutrophication in the Florida Everglades: cross‐system patterns of structural and compositional change. Limnology and Oceanography, 51(1part2), 617-630.\n Moore, J. C., E. L. Berlow, D. C. Coleman, P. C. Ruiter, Q. Dong, A. Hastings, N. C. Johnson, K. S. McCann, K. Melville, P. J. Morin, K. Nadelhoffer, A. D. Rosemond, D. M. Post, J. L. Sabo, K. M. Scow, M. J. Vanni, and D. H. Wall. 2004. Detritus, trophic dynamics and biodiversity: Detritus, trophic dynamics and biodiversity. Ecology Letters 7:584–600. \n Naja, M., Childers, D. L., & Gaiser, E. E. (2017). Water quality implications of hydrologic restoration alternatives in the Florida Everglades, United States. Restoration Ecology, 25, S48-S58.\n Schmitz, O. J., Kalies, E. L., & Booth, M. G. (2006). Alternative dynamic regimes and trophic control of plant succession. Ecosystems, 9, 659-672.\n Schulte, Nicholas O., "Controls on Benthic Microbial Community Structure and Assembly in a Karstic Coastal Wetland" (2016). FIU Electronic Theses and Dissertations. 2447. 10.25148/etd.FIDC000233\n Trexler, J. C., Gaiser, E. E., Kominoski, J. S., & Sanchez, J. (2015). The role of periphyton mats in consumer community structure and function in calcareous wetlands: lessons from the Everglades. Microbiology of the everglades ecosystem, 155-179."]} 

   more » « less