A high-resolution synthetic bed elevation grid of the Antarctic continent
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Published:2017-05-05
Issue:1
Volume:9
Page:267-279
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ISSN:1866-3516
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Container-title:Earth System Science Data
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language:en
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Short-container-title:Earth Syst. Sci. Data
Author:
Graham Felicity S.ORCID, Roberts Jason L.ORCID, Galton-Fenzi Ben K.ORCID, Young DuncanORCID, Blankenship Donald, Siegert Martin J.ORCID
Abstract
Abstract. Digital elevation models of Antarctic bed topography are smoothed and interpolated onto low-resolution ( > 1 km) grids as current observed topography data are generally sparsely and unevenly sampled. This issue has potential implications for numerical simulations of ice-sheet dynamics, especially in regions prone to instability where detailed knowledge of the topography, including fine-scale roughness, is required. Here, we present a high-resolution (100 m) synthetic bed elevation terrain for Antarctica, encompassing the continent, continental shelf, and seas south of 60° S. Although not identically matching observations, the synthetic bed surface – denoted as HRES – preserves topographic roughness characteristics of airborne and ground-based ice-penetrating radar data measured by the ICECAP (Investigating the Cryospheric Evolution of the Central Antarctic Plate) consortium or used to create the Bedmap1 compilation. Broad-scale ( > 5 km resolution) features of the Antarctic landscape are incorporated using a low-pass filter of the Bedmap2 bed elevation data. HRES has applicability in high-resolution ice-sheet modelling studies, including investigations of the interaction between topography, ice-sheet dynamics, and hydrology, where processes are highly sensitive to bed elevations and fine-scale roughness. The data are available for download from the Australian Antarctic Data Centre (doi:10.4225/15/57464ADE22F50).
Publisher
Copernicus GmbH
Subject
General Earth and Planetary Sciences
Reference34 articles.
1. Alabert, F.: The practice of fast conditional simulations through the LU decomposition of the covariance matrix, Math. Geol., 19, 369–386, https://doi.org/10.1007/BF00897191, 1987. 2. Blankenship, D. D., Kempf, S. D., Young, D. A., Richter, T. G., Schroeder, D. M., Greenbaum, J. S., Holt, J. W., van Ommen, T. D., Warner, R. C., Roberts, J. L., Young, N. W., Lemeur, E., and Siegert, M. J.: IceBridge HiCARS 1 L2 geolocated ice thickness, Version 1, NASA National Snow and Ice Data Center Distributed Active Archive Center, https://doi.org/10.5067/F5FGUT9F5089, 2011. 3. Blankenship, D. D., Kempf, S. D., Young, D. A., Richter, T. G., Schroeder, D. M., Ng, G., Greenbaum, J. S., van Ommen, T. D., Warner, R. C., Roberts, J. L., Young, N. W., Lemeur, E., and Siegert, M. J.: IceBridge HiCARS 1 L2 geolocated ice thickness, Version 1, NASA National Snow and Ice Data Center Distributed Active Archive Center, https://doi.org/10.5067/9EBR2T0VXUDG, 2012. 4. Bourgault, G.: Using non-Gaussian distributions in geostatistical simulations, Math. Geol., 29, 315–334, https://doi.org/10.1007/BF02769638, 1997. 5. Church, J. A., Clark, P. U., Cazenave, A., Gregory, J. M., Jevrejeva, S., Levermann, A., Merrifield, M. A., Milne, G. A., Nerem, R. S., Nunn, P. D., Payne, A. J., Pfeffer, W. T., Stammer, D., and Unnikrishnan, A. S.: Sea level change, Tech. rep., IPCC, https://doi.org/10.1017/CBO9781107415324.026, 2013.
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