Seismic wave propagation in anisotropic ice – Part 2: Effects of crystal anisotropy in geophysical data

Diez, Anja; Eisen, Olaf; Hofstede, Coen; Lambrecht, Astrid; Mayer, Christoph; Miller, Heinz; Steinhage, Daniel; Binder, Tobias; Weikusat, Ilka

doi:10.5194/tc-9-385-2015

Cited by 42 publications

(27 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The single maximum LPO along the vertical core axis is fully developed after a sudden final collapse of the girdle between 2035 and 2045 m. This sudden change in the LPO was also detected as a clear reflector in radio-echo sounding (RES) data, which is caused by the dependence of the electromagnetic wave velocity from the crystallographic orientation [98–100]. Grain elongation direction histograms derived from vertical sections (figure 5 b left) show a broad, but distinct distribution (cone angle of 45°) with a slight tendency towards double/multiple maxima.…”

Section: Discussionmentioning

confidence: 99%

Physical analysis of an Antarctic ice core—towards an integration of micro- and macrodynamics of polar ice

Weikusat

Jansen

Binder

et al. 2017

Phil. Trans. R. Soc. A.

Self Cite

View full text Add to dashboard Cite

Microstructures from deep ice cores reflect the dynamic conditions of the drill location as well as the thermodynamic history of the drill site and catchment area in great detail. Ice core parameters (crystal lattice-preferred orientation (LPO), grain size, grain shape), mesostructures (visual stratigraphy) as well as borehole deformation were measured in a deep ice core drilled at Kohnen Station, Dronning Maud Land (DML), Antarctica. These observations are used to characterize the local dynamic setting and its rheological as well as microstructural effects at the EDML ice core drilling site (European Project for Ice Coring in Antarctica in DML). The results suggest a division of the core into five distinct sections, interpreted as the effects of changing deformation boundary conditions from triaxial deformation with horizontal extension to bedrock-parallel shear. Region 1 (uppermost approx. 450 m depth) with still small macroscopic strain is dominated by compression of bubbles and strong strain and recrystallization localization. Region 2 (approx. 450–1700 m depth) shows a girdle-type LPO with the girdle plane being perpendicular to grain elongations, which indicates triaxial deformation with dominating horizontal extension. In this region (approx. 1000 m depth), the first subtle traces of shear deformation are observed in the shape-preferred orientation (SPO) by inclination of the grain elongation. Region 3 (approx. 1700–2030 m depth) represents a transitional regime between triaxial deformation and dominance of shear, which becomes apparent in the progression of the girdle to a single maximum LPO and increasing obliqueness of grain elongations. The fully developed single maximum LPO in region 4 (approx. 2030–2385 m depth) is an indicator of shear dominance. Region 5 (below approx. 2385 m depth) is marked by signs of strong shear, such as strong SPO values of grain elongation and strong kink folding of visual layers. The details of structural observations are compared with results from a numerical ice sheet model (PISM, isotropic) for comparison of strain rate trends predicted from the large-scale geometry of the ice sheet and borehole logging data. This comparison confirms the segmentation into these depth regions and in turn provides a wider view of the ice sheet.This article is part of the themed issue ‘Microdynamics of ice’.

show abstract

Section: Discussionmentioning

confidence: 99%

Physical analysis of an Antarctic ice core—towards an integration of micro- and macrodynamics of polar ice

Weikusat

Jansen

Binder

et al. 2017

Phil. Trans. R. Soc. A.

Self Cite

View full text Add to dashboard Cite

show abstract

“…This classification introduces artificial discontinuities in the velocity profile over depth, calculated from an ice core. These discontinuities only reflect the calculation method, not sudden changes in the prevailing fabric (Part II, Diez et al, 2015). This limitation, introduced by the classification of the different fabric groups, could be overcome by calculating the opening angels directly from the derived c axis vectors.…”

Section: Limitations Of the Methodsmentioning

confidence: 99%

“…Different authors have measured (Jona and Scherrer, 1952;Green and Mackinnen, 1956;Bass et al, 1957;Brockamp and Querfurth, 1964;Bennett, 1968;Dantl, 1968;Gammon et al, 1983) and calculated (Penny, 1948) the monocrystal elasticity tensor. A comparison of the different elasticity tensors used can be found in Part II (Diez et al, 2015). There we investigate results of a vertical seismic profiling survey in comparison to quantities from measured COF eigenvalues.…”

Section: Limitations Of the Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Seismic wave propagation in anisotropic ice – Part 1: Elasticity tensor and derived quantities from ice-core properties

Diez

Eisen

2015

The Cryosphere

Self Cite

View full text Add to dashboard Cite

Abstract.A preferred orientation of the anisotropic ice crystals influences the viscosity of the ice bulk and the dynamic behaviour of glaciers and ice sheets. Knowledge about the distribution of crystal anisotropy is mainly provided by crystal orientation fabric (COF) data from ice cores. However, the developed anisotropic fabric influences not only the flow behaviour of ice but also the propagation of seismic waves. Two effects are important: (i) sudden changes in COF lead to englacial reflections, and (ii) the anisotropic fabric induces an angle dependency on the seismic velocities and, thus, recorded travel times. A framework is presented here to connect COF data from ice cores with the elasticity tensor to determine seismic velocities and reflection coefficients for cone and girdle fabrics. We connect the microscopic anisotropy of the crystals with the macroscopic anisotropy of the ice mass, observable with seismic methods. Elasticity tensors for different fabrics are calculated and used to investigate the influence of the anisotropic ice fabric on seismic velocities and reflection coefficients, englacially as well as for the ice-bed contact. Hence, it is possible to remotely determine the bulk ice anisotropy.

show abstract

“…The elastic modulus of snow is a fundamental mechanical property relating stress and strain. It is a highly relevant parameter for many snow mechanical application covering engineering aspects of tire traction (Choi et al, 2012), interpretation of seismic waves (Diez et al, 2015), snow fracture in relation to avalanche release (Van Herwijnen et al, 2016), or the validation of new constitutive models (Barraclough et al, 2017). Snow is a fragile, porous material that exists close to its melting point, making it highly rate dependent with a strong microstructural influence.…”

Section: Introductionmentioning

confidence: 99%

Measuring the Elastic Modulus of Snow

Gerling¹,

Löwe²,

Herwijnen³

2017

Geophysical Research Letters

View full text Add to dashboard Cite

The elastic modulus is the most fundamental mechanical property of snow. However, literature values scatter by orders of magnitude and hitherto no cross-validated measurements exists. To this end, we employ P wave propagation experiments under controlled laboratory conditions on decimeter-sized snow specimen, prepared from artificial snow and subjected to isothermal sintering, to cover a considerable range of densities (170-370 kg m −3). The P wave modulus was estimated from wave propagation speeds in transverse isotropic media and compared to microstructure-based finite element (FE) calculations from X-ray tomography images. Heterogeneities and size differences between acoustic and FE sample volumes were characterized by SnowMicroPen measurements, yielding an elastic modulus as a by-product. The moduli (10-340 MPa) from the acoustic and FE method are in very good agreement (R 2 = 0.99) over the entire range of densities. A remaining bias (24 %) between both methods can be explained by layer heterogeneities which systematically reduce the estimates from the acoustic method.

show abstract

Seismic wave propagation in anisotropic ice – Part 2: Effects of crystal anisotropy in geophysical data

Cited by 42 publications

References 22 publications

Physical analysis of an Antarctic ice core—towards an integration of micro- and macrodynamics of polar ice

Physical analysis of an Antarctic ice core—towards an integration of micro- and macrodynamics of polar ice

Seismic wave propagation in anisotropic ice – Part 1: Elasticity tensor and derived quantities from ice-core properties

Measuring the Elastic Modulus of Snow

Contact Info

Product

Resources

About