Basal roughness of the East Antarctic Ice Sheet in relation to flow speed and basal thermal state

Eisen, Olaf; Winter, Anna; Steinhage, Daniel; Kleiner, Thomas; Humbert, Angelika

doi:10.1017/aog.2020.47

Cited by 16 publications

(42 citation statements)

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“…As mapped across a number of regions of Antarctica and Greenland, roughness variations at the multi-kilometer scale inform us about present and past ice-stream and ice-stream tributary locations (Siegert and others, 2004; Bingham and Siegert, 2007, 2009; Rippin and others, 2014; Frank and others, 2020). Additionally, basal roughness at the wavelength-scale can affect the character of the reflected echo including its specularity (or spread in Doppler), waveform abruptness, statistical distribution of echo amplitudes, as well as the radar-derived topography itself (Goff and others, 2014; Grima and others, 2014a; Rippin and others, 2014; Schroeder and others, 2014a; Jordan and others, 2017; Heister and Scheiber, 2018; Eisen and others, 2020; Franke and others, 2020; King, 2020). Principles from these studies have also been translated to paleoglacial landscapes and have also been compared to contemporary bed morphology and lithology (Gudlaugsson and others, 2013; Schroeder and others, 2014c; Falcini and others, 2018; Cooper and others, 2019; Muto and others, 2019; Holschuh and others, 2020).…”

Section: Ice Sheet and Glacier Bed Conditionsmentioning

confidence: 99%

Five decades of radioglaciology

et al. 2020

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Radar sounding is a powerful geophysical approach for characterizing the subsurface conditions of terrestrial and planetary ice masses at local to global scales. As a result, a wide array of orbital, airborne, ground-based, and in situ instruments, platforms and data analysis approaches for radioglaciology have been developed, applied or proposed. Terrestrially, airborne radar sounding has been used in glaciology to observe ice thickness, basal topography and englacial layers for five decades. More recently, radar sounding data have also been exploited to estimate the extent and configuration of subglacial water, the geometry of subglacial bedforms and the subglacial and englacial thermal states of ice sheets. Planetary radar sounders have observed, or are planned to observe, the subsurfaces and near-surfaces of Mars, Earth's Moon, comets and the icy moons of Jupiter. In this review paper, and the thematic issue of the Annals of Glaciology on ‘Five decades of radioglaciology’ to which it belongs, we present recent advances in the fields of radar systems, missions, signal processing, data analysis, modeling and scientific interpretation. Our review presents progress in these fields since the last radio-glaciological Annals of Glaciology issue of 2014, the context of their history and future prospects.

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Section: Ice Sheet and Glacier Bed Conditionsmentioning

confidence: 99%

Five decades of radioglaciology

et al. 2020

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“…The majority of subglacial roughness studies in Antarctica focus on outlet glaciers (Bingham & Siegert, 2007, 2009; Diez et al., 2018; MacGregor et al., 2013; Rippin et al., 2011, 2014, 2006; Taylor et al., 2004) with only a few studies extending over large areas (e.g., Eisen et al. [2020] in East Antarctica). In a study to model the surface flow field of Pine Island Glacier, Wilkens et al.…”

Section: Introductionmentioning

confidence: 99%

Complex Basal Conditions and Their Influence on Ice Flow at the Onset of the Northeast Greenland Ice Stream

et al. 2021

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The lack of high-resolution bed topography and knowledge about the subglacial conditions in Greenland and Antarctica is one of the largest sources of uncertainty in present ice sheet projections (Morlighem et al., 2019) and higher resolution bed topography is needed to improve the accuracy of ice sheet models (Durand et al., 2011). The subglacial environment of the Antarctic and Greenland Ice Sheet (AIS, GrIS) is only poorly known from direct observations. The technical and logistical efforts for an analysis of the base underneath ice, often several kilometres thick, is much more challenging than observations on paleo-glaciated areas on land or the seafloor through remote sensing techniques (e.g., Clark and Meehan 2001; Stokes et al., 2013) or marine swath bathymetry (e.g., Arndt et al., 2020; Dowdeswell et al., 2004). Most of the knowledge about the ice covered bathymetry, bed topography and basal properties are deduced from the analysis and interpretation of indirect observations like radio-echo sounding (

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“…Mackie and others, 2020; Goff and others, 2014). Clearly, a method that allows bed roughness to be extracted from radar data accurately and efficiently, with maximum information incorporated within the results, would allow it to become better assimilated into assessments of ice dynamics, glacial history and basal conditions (Eisen and others, 2020).…”

Section: Introductionmentioning

confidence: 99%

“…The main methods of quantifying bed roughness from radar data can be divided into two categories: the electromagnetic scattering properties of the bed-echo waveform; and the statistical properties of the along-track topography (Cooper and others, 2019; Eisen and others, 2020).…”

Section: Introductionmentioning

confidence: 99%

“…This requires the investigator to subjectively choose where the beginning and endpoints of each trend occur when a breakpoint is evident (Shepard and others, 2001). Besides that, the ‘Hurst exponent’ results show rapid local fluctuations on maps (Jordan and others, 2017; Eisen and others, 2020), which make it difficult to quantify the large span of terrains.…”

Section: Introductionmentioning

confidence: 99%

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A self-adaptive two-parameter method for characterizing roughness of multi-scale subglacial topography

Lang

Cui

et al. 2021

J. Glaciol.

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During the last few decades, bed-elevation profiles from radar sounders have been used to quantify bed roughness. Various methods have been employed, such as the ‘two-parameter’ technique that considers vertical and slope irregularities in topography, but they struggle to incorporate roughness at multiple spatial scales leading to a breakdown in their depiction of bed roughness where the relief is most complex. In this article, we describe a new algorithm, analogous to wavelet transformations, to quantify the bed roughness at multiple scales. The ‘Self-Adaptive Two-Parameter’ system calculates the roughness of a bed profile using a frequency-domain method, allowing the extraction of three characteristic factors: (1) slope, (2) skewness and (3) coefficient of variation. The multi-scale roughness is derived by weighted-summing of these frequency-related factors. We use idealized bed elevations to initially validate the algorithm, and then actual bed-elevation data are used to compare the new roughness index with other methods. We show the new technique is an effective tool for quantifying bed roughness from radar data, paving the way for improved continental-wide depictions of bed roughness and incorporation of this information into ice flow models.

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Basal roughness of the East Antarctic Ice Sheet in relation to flow speed and basal thermal state

Cited by 16 publications

References 57 publications

Five decades of radioglaciology

Five decades of radioglaciology

Complex Basal Conditions and Their Influence on Ice Flow at the Onset of the Northeast Greenland Ice Stream

A self-adaptive two-parameter method for characterizing roughness of multi-scale subglacial topography

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