Surface Density, Roughness, and Brine Infiltration Observed with Airborne Radar Statistical Reconnaissance at The McMurdo Ice Shelf, Antarctica
Abstract
Radar statistical reconnaissance (RSR) is a recent technique that has been used to characterize the surface properties of the Earth's cryosphere, Mars, and Titan; two forthcoming missions will apply RSR to characterize the surface of Europa, as well. Here we apply RSR to map the surface (snow or ice) density, roughness, and near-surface brine infiltration extent at the McMurdo Ice Shelf (MIS), adjacent to the eponymous station and the Ross Ice Shelf, Antarctica. The ice surface is known for large gradients in snowfall and impurities; however, the MIS is perhaps best known for the presence of brine-soaked firn. Although brine infiltration is known to occur in several Antarctic ice shelves, the process has not been discussed in recent literature despite its importance for the development of englacial microbial habitats or for its potential impact on ice shelf stability. While studies to date have confirmed the existence of brine layers through discrete sampling with ice cores and ground penetrating radar traverses, the active processes that exert primary control on its extent on the MIS has remained elusive.The University of Texas Institute for Geophysics (UTIG) acquired airborne radar survey grids over the northern part of the MIS during the 2011-2012 austral summer then over the remainder of the MIS in summer 2014-2015. Using radar data acquired with the High Capability Radar Sounder (HiCARS2; 60-MHz center frequency and 15-MHz bandwidth), surface density and roughness is quantified with RSR and ice thickness is computed with traditional radar sounding analysis. We present recently-published results from the 2011/2012 campaign to demonstrate that brine infiltration in the northern part of the MIS is primarily controlled by patterns of local snow accumulation. We extend these methodologies to the 2014/2015 data over the Southern MIS (SMIS) to show that RSR-derived snow density values and patterns agree with directly-measured accumulation rates. We also compare the composition of SMIS ice surface samples to test the ability of RSR to discriminate ices with varying dielectric properties (e.g. marine vs meteoric ice). RSR products (e.g. roughness, density, material discrimination) can be used to improve our understanding of planetary ice masses, ice mass balance, and atmosphere-snow-ice interactions.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2016
- Bibcode:
- 2016AGUFM.C53A0701G
- Keywords:
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- 0726 Ice sheets;
- CRYOSPHEREDE: 0758 Remote sensing;
- CRYOSPHEREDE: 0798 Modeling;
- CRYOSPHEREDE: 1621 Cryospheric change;
- GLOBAL CHANGE