Abstract 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. Each model experiment yields an optimal friction coefficient in the sliding law of 10 − 5 M P a ⋅ a m , while estimates of the optimal von Mises stress threshold for crevasse initiation ranged between 230 and 240 k P a .

中文翻译：

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冰川高程分析和数值模拟对 CryoSat-2 SIRAL 再跟踪技术的敏感性

摘要 2010 年发射的 CryoSat-2 雷达测高任务提供了地球冰冻圈的关键测量值。CryoSat-2 的主要仪器是合成孔径干涉雷达高度计 (SIRAL)，可以准确测量倾斜冰面的高度，包括阿拉斯加东南部高度裂缝的白令-巴格利冰川系统 (BBGS)。最近 2011-2013 年 BBGS 的激增导致了大规模的高程变化和广泛的裂缝，对 SIRAL 测量的处理提出了有趣的挑战。表面高度的推导是通过重新跟踪接收到的高度计信号的波形来实现的。已经开发了几种这样的重新跟踪方法。在本文中，我们研究了六种独特的 SIRAL 重跟踪方法对 (1) 数字高程模型 (DEM) 生成的影响，(2) 冰面地形分析，以及 (3) BBGS 在涌浪过程中的数值模拟结果。首先，我们使用克里金法为每个重新跟踪的数据集导出表面 DEM。经过条带处理的数据集提供的点数是其他数据集的 100-250 倍，这将与数据覆盖率相关的 DEM 不确定性降低了 2-4 倍。六个生成的 DEM 之间的差异意味着重新跟踪方法可以对高程和高程变化分析产生显着影响，但我们发现较低级别的处理具有更大的影响。接下来，使用 BBGS 浪涌的有限元模型评估数据模型连接的敏感性。我们设置了六个建模实验，每个实验都以一个独特的输入表面 DEM 启动，该输入表面 DEM 源自各种重新跟踪方法。在重新跟踪与裂缝模拟相关的未知模型参数的选择影响估计时，我们开发了一个程序来限制这些影响，从而在整个建模实验中实现非常一致的参数优化。每个模型实验在 10 − 5 MP a ⋅ am 的滑动定律中产生最佳摩擦系数，而裂隙起始的最佳 von Mises 应力阈值的估计值介于 230 和 240 k Pa 之间。