Abstract:The Bering Glacier–Bagley Icefield system in Alaska is currently surging (2011). Large-scale elevation changes and small-scale elevation-change characteristics are investigated to understand surge progression, especially mass transport from the pre-surge reservoir area to the receiving area and propagation of the kinematic surge wave as manifested in heavy crevassing characteristic of rapid, brittle deformation. This analysis is based on airborne laser altimeter data collected over Bering Glacier in September … Show more
“…This figure also shows the model domain, defined to include the surging parts of the BBGS. The main Bering Glacier is a surge‐type glacier (Post, ); the surge dynamics extends into the Eastern Bagley Ice Field, also named Bagley Ice Valley, as noted in 1995 (Herzfeld & Mayer, ) and observed again in 2011–2013 (Herzfeld, McDonald, Stachura, et al, ; Herzfeld, McDonald, & Weltman, ), while the Western Bagley Ice Field is not affected by the surge process. The neighboring Steller Glacier originates in the Western Bagley Ice Field and shares a medial moraine with the lobe of Bering Glacier.…”
Section: The Bering‐bagley Glacier System: Geography and Surge Historymentioning
confidence: 99%
“…Airborne imagery collected in our Fall 2011 campaign to the BBGS (Herzfeld et al, ) is given in Figure , which shows the locations that were most affected by the early‐2011 phase of the surge. The flightpath for our Fall 2011 campaign is marked by the thin black line in Figure b.…”
Section: The Bering‐bagley Glacier System: Geography and Surge Historymentioning
confidence: 99%
“…As observed in Herzfeld and Mayer (), Herzfeld (), and (Herzfeld et al, ), the first visible surface expression of the surge's kinematic wave is an occurrence of bidirectional crevasses with sharp edges in regions of high surface slope, indicative of bedrock slope. The reason is that the kinematic force of the surge breaks first at preexisting weaknesses caused by already crevassed ice or over relatively thin ice.…”
Section: Effects Of Bedrock Topography On Surface Crevassingmentioning
confidence: 99%
“…The 2011-2013 surge in the Bering Bagley Glacier System (BBGS), Alaska, has provided an opportunity for data collection and analysis of the surge phenomenon in a large and complex glacier system (Herzfeld, McDonald, Stachura, et al, 2013;Herzfeld, McDonald, & Weltman, 2013;Trantow & Herzfeld, 2016). The BBGS is one of the largest glacial systems outside of Greenland and Antarctica and the largest temperate surge-type glacier on Earth (Molnia, 2008).…”
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.
“…This figure also shows the model domain, defined to include the surging parts of the BBGS. The main Bering Glacier is a surge‐type glacier (Post, ); the surge dynamics extends into the Eastern Bagley Ice Field, also named Bagley Ice Valley, as noted in 1995 (Herzfeld & Mayer, ) and observed again in 2011–2013 (Herzfeld, McDonald, Stachura, et al, ; Herzfeld, McDonald, & Weltman, ), while the Western Bagley Ice Field is not affected by the surge process. The neighboring Steller Glacier originates in the Western Bagley Ice Field and shares a medial moraine with the lobe of Bering Glacier.…”
Section: The Bering‐bagley Glacier System: Geography and Surge Historymentioning
confidence: 99%
“…Airborne imagery collected in our Fall 2011 campaign to the BBGS (Herzfeld et al, ) is given in Figure , which shows the locations that were most affected by the early‐2011 phase of the surge. The flightpath for our Fall 2011 campaign is marked by the thin black line in Figure b.…”
Section: The Bering‐bagley Glacier System: Geography and Surge Historymentioning
confidence: 99%
“…As observed in Herzfeld and Mayer (), Herzfeld (), and (Herzfeld et al, ), the first visible surface expression of the surge's kinematic wave is an occurrence of bidirectional crevasses with sharp edges in regions of high surface slope, indicative of bedrock slope. The reason is that the kinematic force of the surge breaks first at preexisting weaknesses caused by already crevassed ice or over relatively thin ice.…”
Section: Effects Of Bedrock Topography On Surface Crevassingmentioning
confidence: 99%
“…The 2011-2013 surge in the Bering Bagley Glacier System (BBGS), Alaska, has provided an opportunity for data collection and analysis of the surge phenomenon in a large and complex glacier system (Herzfeld, McDonald, Stachura, et al, 2013;Herzfeld, McDonald, & Weltman, 2013;Trantow & Herzfeld, 2016). The BBGS is one of the largest glacial systems outside of Greenland and Antarctica and the largest temperate surge-type glacier on Earth (Molnia, 2008).…”
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.
“…The analysis and classification of crevassed ice surfaces from images collected during the current (2011) surge of the Bering-Bagley glacier system forms a central part of the paper. The vertical component of the surge kinematics can be constrained using analysis of laser altimeter data (Herzfeld and others, 2013).…”
Section: Introduction: the Problem Of Understanding Surge Progressionmentioning
The dynamics of a surge is manifested in the crevasse patterns: literally, deformation state frozen in ice. This basic observation is utilized as the concept of an automated approach to map and analyze deformation stages and progression of surge kinematics. The classification method allows imagery to be used as geophysical data and is applied to aerial observations (photographic and video imagery, GPS data) collected in September 2011 during the surge of the Bering Glacier–Bagley Ice Valley system, Alaska, USA. As the third dimension that complements two-dimensional imagery, ice-surface elevation is observed using aerial laser altimetry. The classification method builds on concepts from signal processing, geostatistical data analysis and neural networks. Steps include calculation of generalized directional vario functions from image data and composition into feature vectors. The vario function operates as an information filter that retains spatial characteristics at an intermediate scale that captures crevasse spacing, anisotropy and other generalized roughness properties. Association of feature vectors to crevasse classes and hence deformation types employs a connectionist algorithm. In general, the connectionist–geostatistical classification allows the mapping of kinematic changes in crevassed glaciers.Dedicated to the memory of Austin Post
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