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Abstract Spatial variability in bed topography, characterized as bed roughness, impacts ice-sheet flow and organization and can be used to infer subglacial conditions and processes, yet is difficult to quantify due to sparse observations. Paleo-subglacial beds of formerly expanded glaciers found across the Antarctic continental shelf are well preserved, have relatively limited post-glacial sediment cover and contain glacial landforms that can be resolved at sub-meter vertical scales. We analyze high-resolution bathymetry offshore of Pine Island and Thwaites glaciers in the Amundsen Sea to explore spatial variability of bed roughness where streamlined subglacial landforms allow for the determination of ice-flow direction. We quantify bed roughness using std dev. and Fast Fourier Transform methods, each employed at local (100km) and regional (101–2km) scales and in along- and across-flow orientations to determine roughness expressions across spatial scales. We find that the magnitude of roughness is impacted by the parameters selected – which are often not sufficiently reported in studies – to quantify roughness. Important spatial patterns can be discerned from high-resolution bathymetry, highlighting both its usefulness in identifying patterns of streaming ice flow and underscores the need for a standardized way of characterizing topographic variability.
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How Many Parameters are Needed to Represent Polar Sea Ice Surface Patterns and Heterogeneity?
Sea ice surface patterns encode more information than can be represented solely by the ice fraction. The aim of this paper is thus to establish the importance of using a broader set of surface characterization metrics, and to identify a minimal set of such metrics that may be useful for representing sea-ice in Earth System Models. Large-eddy simulations of the atmospheric boundary layer over various idealized sea ice surface patterns, with equivalent ice fraction and average floe area, demonstrate that the spatial organization of ice and water can play a crucial role in determining boundary-layer structure. Thus, different methods to quantify heterogeneity in categorical lattice spatial data, such as those done in landscape ecology and Geographic Information System (GIS) studies, are used here on a set of high-resolution, recently-declassified sea ice surface images. It is found that, in conjunction with ice fraction, the patch density (representing the fragmentation of the surface), the splitting index (representing the variability in patch size), and perimeter-area fractal dimension (representing the tortuosity of the interface) are all required to describe the two-dimensional pattern exhibited by a sea ice surface. Furthermore, for surfaces with anisotropic patterns, the orientation of the surface relative to the mean wind is needed. Furthermore, scaling laws are derived for these relevant landscape metrics to estimate them from aggregated spatial sea ice surface data at any resolution. The methods used and results gained from this study are a first step towards further development of methods to quantify the variability of non-binary surfaces, and for parameterizing mixed ice-water surfaces in coarse geophysical models.
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- Award ID(s):
- 2128345
- PAR ID:
- 10539553
- Publisher / Repository:
- European Geophysical Union
- Date Published:
- Format(s):
- Medium: X
- Institution:
- Princeton University
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Posted Content:
- https://doi.org/10.5194/egusphere-2024-532
