One of the largest sources of uncertainty in sea level rise prediction is glacial acceleration, of which the surge phenomenon is the least understood type. The surge of the Bering Bagley Glacier System (BBGS), Alaska, in 2011–2013 has provided a rare opportunity to study the surge phenomenon in a large and complex glacier system. A surge results in widespread crevassing throughout the glacier system complicating many traditional techniques used to study glacier dynamics. In this paper, we utilize crevassing as a means to investigate the recent BBGS surge through numerical modeling and geostatistical data analysis. Following the principles of structural glaciology, image‐based crevasse characterizations are obtained through geostatistical methods applied to Landsat‐7 data, supplemented by airborne field observations. On the modeling side, a 3‐D full‐Stokes finite element model of the BBGS is developed and applied to investigate ice dynamics and surface structures during the recent surge. A von Mises criterion is adopted to simulate crevassing at the glacier surface, oriented along the axes of maximum principal tensile stress. To facilitate evaluation of model‐ and data‐derived crevasse characteristics, three different comparison methods are introduced. General agreement in the model‐data comparisons indicates that the model has the ability to represent the BBGS system during peak acceleration. The crevasse‐based approach is also employed to optimize the basal sliding parameter and the von Mises stress threshold in the model. Results further indicate that bed topography is an important constraint in modeling the surge process.

https://doi.org/10.1029/2017JF004341

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