generating synthetic fjord bathymetry for coastal greenland

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ID: 233234
2017
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Abstract
Bed topography is a critical boundary for the numerical modelling of ice sheets and ice–ocean interactions. A persistent issue with existing topography products for the bed of the Greenland Ice Sheet and surrounding sea floor is the poor representation of coastal bathymetry, especially in regions of floating ice and near the grounding line. Sparse data coverage, and the resultant coarse resolution at the ice–ocean boundary, poses issues in our ability to model ice flow advance and retreat from the present position. In addition, as fjord bathymetry is known to exert strong control on ocean circulation and ice–ocean forcing, the lack of bed data leads to an inability to model these processes adequately. Since the release of the last complete Greenland bed topography–bathymetry product, new observational bathymetry data have become available. These data can be used to constrain bathymetry, but many fjords remain completely unsampled and therefore poorly resolved. Here, as part of the development of the next generation of Greenland bed topography products, we present a new method for constraining the bathymetry of fjord systems in regions where data coverage is sparse. For these cases, we generate synthetic fjord geometries using a method conditioned by surveys of terrestrial glacial valleys as well as existing sinuous feature interpolation schemes. Our approach enables the capture of the general bathymetry profile of a fjord in north-west Greenland close to Cape York, when compared to observational data. We validate our synthetic approach by demonstrating reduced overestimation of depths compared to past attempts to constrain fjord bathymetry. We also present an analysis of the spectral characteristics of fjord centrelines using recently acquired bathymetric observations, demonstrating how a stochastic model of fjord bathymetry could be parameterised and used to create different realisations.
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williams2017thegenerating Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;C. N. Williams;S. L. Cornford;T. M. Jordan;J. A. Dowdeswell;M. J. Siegert;C. D. Clark;D. A. Swift;A. Sole;I. Fenty;J. L. Bamber
Journal journal of applied polymer science
Year 2017
DOI
10.5194/tc-11-363-2017
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