Effects of Birefringence Within Ice Sheets on Obliquely Propagating Radio Waves

Matsuoka, Kenichi; Wilen, Larry; Hurley, Shawn; Raymond, C. F.

doi:10.1109/tgrs.2008.2005201

Cited by 49 publications

(81 citation statements)

References 46 publications

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“…Several authors have confirmed the relationship between the echo difference in orthogonal directions and the permittivity tensor of ice (Hargreaves 1977;Fujita et al 2006;Matsuoka et al 2012), which is linked to the second-order tensor of ice fabric (Matsuoka et al 2009). Hence, in the absence of plausible alternative explanations, it can be assumed that the Stokes vector parameter description of the polarimetric radar reflections S 1 , S 2 and S 3 expresses ice-sheet anisotropy caused by ice crystal fabric.…”

Section: Polarimetric Radio Waves and Stokes Parametersmentioning

confidence: 88%

“…Unit T 2 (positive S 1 ) is up to c. 400 m thick and contains an abundance of highly anisotropic ice related to a vertical girdle fabric distribution. T 3 (negative S 1 ) is a product of low levels of horizontal anisotropy, as the fabric clusters towards a broad single-pole distribution (Hargreaves 1977;Eisen et al 2007;Matsuoka et al 2009). T 4 (highly positive S 1 ) is similar in crystal arrangement to T 2 .…”

Section: Radar Surveymentioning

confidence: 99%

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Summit of the East Antarctic Ice Sheet underlain by thick ice-crystal fabric layers linked to glacial–interglacial environmental change

Wang

Sun

Martín

et al. 2017

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Ice cores in Antarctica and Greenland reveal ice-crystal fabrics that can be softer under simple shear compared with isotropic ice. Owing to the sparseness of ice cores in regions away from the ice divide, we currently lack information about the spatial distribution of ice fabrics and its association with ice flow. Radio-wave reflections are influenced by ice-crystal alignments, allowing them to be tracked provided reflections are recorded simultaneously in orthogonal orientations (polarimetric measurements). Here, we image spatial variations in the thickness and extent of ice fabric across Dome A in East Antarctica, by interpreting polarimetric radar data. We identify four prominent fabric units, each several hundred metres thick, extending over hundreds of square kilometres. By tracing internal ice-sheet layering to the Vostok ice core, we are able to determine the approximate depth-age profile at Dome A. The fabric units correlate with glacial-interglacial cycles, most noticeably revealing crystal alignment contrasts between the Eemian and the glacial episodes before and after. The anisotropy within these fabric layers has a spatial pattern determined by ice flow over subglacial topography.Gold Open Access: This article is published under the terms of the CC-BY 3.0 license.

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Section: Polarimetric Radio Waves and Stokes Parametersmentioning

confidence: 88%

Section: Radar Surveymentioning

confidence: 99%

Summit of the East Antarctic Ice Sheet underlain by thick ice-crystal fabric layers linked to glacial–interglacial environmental change

Wang

Sun

Martín

et al. 2017

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“…Remote sensing methods provide therefore a complementary tool to the detailed ground measurements such as CT or in situ measurements. For example, radio-wave birefringence measurements have been used to explore internal structures of ice sheets and glaciers with polarized radio-and microwaves (e.g., Hargreaves, 1977Hargreaves, , 1978Fujita et al, 2006;Matsuoka et al, 2009;Parrella et al, 2016). With passive microwave sensors, strong polarimetric signatures have also been found over the Greenland ice sheet: in Li et al (2008), the observed signatures could not be explained by surface features and were discussed with respect to microstructural variations of snow anisotropy, as predicted by Tsang (1991).…”

Section: Radio and Microwave Remote Sensing Observations Of The Dielementioning

confidence: 99%

Anisotropy of seasonal snow measured by polarimetric phase differences in radar time series

Leinß

Löwe²,

Proksch³

et al. 2016

The Cryosphere

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Abstract. The snow microstructure, i.e., the spatial distribution of ice and pores, generally shows an anisotropy which is driven by gravity and temperature gradients and commonly determined from stereology or computer tomography. This structural anisotropy induces anisotropic mechanical, thermal, and dielectric properties. We present a method based on radio-wave birefringence to determine the depth-averaged, dielectric anisotropy of seasonal snow with radar instruments from space, air, or ground. For known snow depth and density, the birefringence allows determination of the dielectric anisotropy by measuring the copolar phase difference (CPD) between linearly polarized microwaves propagating obliquely through the snowpack. The dielectric and structural anisotropy are linked by MaxwellGarnett-type mixing formulas. The anisotropy evolution of a natural snowpack in Northern Finland was observed over four winters (2009)(2010)(2011)(2012)(2013) with the ground-based radar instrument "SnowScat". The radar measurements indicate horizontal structures for fresh snow and vertical structures in old snow which is confirmed by computer tomographic in situ measurements. The temporal evolution of the CPD agreed in ground-based data compared to space-borne measurements from the satellite TerraSAR-X. The presented dataset provides a valuable basis for the development of new snow metamorphism models which include the anisotropy of the snow microstructure.

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“…This opens up the possibility for more sophisticated radar-wave velocity models including ice anisotropy originating from aligned crystal orientation fabric below the firn-ice transition (Drews et al, 2012;Matsuoka et al, 2012b). The radar data set is also suited for other glaciological applications, for example, using the basal reflections for deriving ice temperature (via radar attenuation rates) from an amplitude versus offset analysis (Winebrenner et al, 2003) and constraining the alignment of ice crystals using multistatic radar as a large-scale Rigsby stage (Matsuoka et al, 2009). …”

Section: Benefits Of Traveltime Inversion Using Ray Tracingmentioning

confidence: 99%

Constraining variable density of ice shelves using wide-angle radar measurements

Drews

Brown²,

Matsuoka

et al. 2016

The Cryosphere

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Abstract. The thickness of ice shelves, a basic parameter for mass balance estimates, is typically inferred using hydrostatic equilibrium, for which knowledge of the depthaveraged density is essential. The densification from snow to ice depends on a number of local factors (e.g., temperature and surface mass balance) causing spatial and temporal variations in density-depth profiles. However, direct measurements of firn density are sparse, requiring substantial logistical effort. Here, we infer density from radio-wave propagation speed using ground-based wide-angle radar data sets (10 MHz) collected at five sites on Roi Baudouin Ice Shelf (RBIS), Dronning Maud Land, Antarctica. We reconstruct depth to internal reflectors, local ice thickness, and firn-air content using a novel algorithm that includes traveltime inversion and ray tracing with a prescribed shape of the depthdensity relationship. For the particular case of an ice-shelf channel, where ice thickness and surface slope change substantially over a few kilometers, the radar data suggest that firn inside the channel is about 5 % denser than outside the channel. Although this density difference is at the detection limit of the radar, it is consistent with a similar density anomaly reconstructed from optical televiewing, which reveals that the firn inside the channel is 4.7 % denser than that outside the channel. Hydrostatic ice thickness calculations used for determining basal melt rates should account for the denser firn in ice-shelf channels. The radar method presented here is robust and can easily be adapted to different radar frequencies and data-acquisition geometries.

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Effects of Birefringence Within Ice Sheets on Obliquely Propagating Radio Waves

Cited by 49 publications

References 46 publications

Summit of the East Antarctic Ice Sheet underlain by thick ice-crystal fabric layers linked to glacial–interglacial environmental change

Summit of the East Antarctic Ice Sheet underlain by thick ice-crystal fabric layers linked to glacial–interglacial environmental change

Anisotropy of seasonal snow measured by polarimetric phase differences in radar time series

Constraining variable density of ice shelves using wide-angle radar measurements

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