Sensitivity of glacier elevation analysis and numerical modeling to CryoSat-2 SIRAL retracking techniques
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Sensitivity of glacier elevation analysis and numerical modeling to CryoSat-2 SIRAL retracking techniques

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  • Journal Title:
    Computers & Geosciences
  • Personal Author:
  • NOAA Program & Office:
    CIRES (Cooperative Institute for Research in Environmental Sciences)
  • Description:
    The CryoSat-2 radar altimetry mission, launched in 2010, provides key measurements of Earth's cryosphere. CryoSat-2's primary instrument, the Synthetic Aperture Interferometric Radar Altimeter (SIRAL), allows accurate height measurements of sloped ice-surfaces including the highly crevassed Bering-Bagley Glacier System (BBGS) in southeast Alaska. The recent surge of the BBGS in 2011–2013, which resulted in large-scale elevation changes and wide-spread crevassing, presents an interesting challenge to the processing of the SIRAL measurements. Derivation of surface height is achieved by retracking the received waveform of the altimeter signal. Several such retracking methods have been developed. In this paper, we investigate the influence of six unique SIRAL retracking methods on (1) Digital Elevation Model (DEM) generation, (2) analysis of ice-surface topography, and (3) numerical modeling results of the BBGS during surge. First, we derive a surface DEM for each retracked dataset using kriging. The swath-processed dataset provides 100–250 times more points than the other datasets, which decreases DEM uncertainty associated with data coverage by a factor of 2–4. Differences between the six resulting DEMs imply that retracking methods can have significant effects on elevation and elevation-change analysis, but we find that lower-level processing has larger effects. Next, the sensitivity of the data-model connection is evaluated using a finite element model of the BBGS surge. We set up six modeling experiments, each initiated with a unique input surface DEM derived from the various retracking methods. While retracking choices effect estimation of unknown model parameters related to crevasse simulation, we have developed a procedure to limit these effects resulting in remarkably consistent parameter optimization across modeling experiments.
  • Source:
    Computers & Geosciences, 146, 104610
  • DOI:
  • ISSN:
    0098-3004
  • Format:
    pdf
  • Publisher:
    Elsevier BV
  • Document Type:
    Journal Article-Accepted Manuscript
  • Rights Information:
    Accepted Manuscript
  • Rights Statement:
    The NOAA IR provides access to this content under the authority of the government's retained license to distribute publications and data resulting from federal funding. While users may legally access this content, the copyright owners retain rights that govern the reproduction, redistribution, and re-use of this work. The user is solely responsible for complying with applicable copyright law.
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