A high-resolution synthetic bed elevation grid of the Antarctic continent

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.

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3