A Surge in a Complex Glacier System: Results from Observations, Data Analysis and Numerical Experiments of the Bering-Bagley Glacier System

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This research project will bring together results from several years of observations of the surge of the Bering-Bagley Glacier System in Alaska BBGS surge and experiments with a finite-element model in order to enhance knowledge of the dynamic within processes in a complex glacier system during a surge.. The Bering-Bagley Glacier System in Alaska is the largest surge-type glacier on Earth and the largest glacier system outside of the Greenland and Antarctic ice sheets. Project results will increase knowledge about the processes that occur during glacial accelerations in Alaska and in the outlet glaciers of the Greenland Ice Sheet, thereby helping to reduce uncertainty in predictions of sea-level rise. The project will provide education and training opportunities for a graduate student and for three undergraduate students from interdisciplinary and diverse backgrounds. The project also will result in the development of education units for direct use in Alaska and Colorado high schools and a web-based curricular unit for schools elsewhere that focuses on the Bering Glacier surges and the surge phenomenon in general.Understanding fast-flowing glaciers and accelerations in ice flow is critical to understanding changes in the cryosphere as well as changes in sea level. Glacial acceleration is the main source of uncertainty in assessment of sea-level rise in the current realm of climatic warming. Surging is the least-studies of the four types of glacial accelerations. Because they suddenly accelerate and advance in a quasi-cyclic and unpredictable manner, surging glaciers are a counterpoint to the seemingly omnipresent retreat in the cryosphere. The current surge of the Bering-Bagley Glacier System provides a rare opportunity to observe and analyze a surge of a large and complex glacier system. This project will include observation, data analysis, data parameterization, and comparison of results from data analysis and model-based numerical experiments. The investigators will analyze data collected during several years of airborne campaigns conducted by the research team together with airborne and satellite laser altimeter and image data from NASA, European Space Agency and commercial satellites and radar data of subglacial topography. The investigators continue their efforts to bring together Earth observations, remote sensing, and numerical modeling. They will apply an automated classification system they previously developed to identify physical parameters from images of crevasse fields. The rapid changes in ice flow during the characteristically different phases of the surge, which often lasts several years although with regionally different slow-downs and accelerations, are manifest in complex crevasse patterns. Derived physical parameters relate directly to deformation and other variables of ice dynamics that are hard to retrieve otherwise but necessary for physical modeling. The image-based classification method is expected to be generally applicable in other areas of environmental and spatial sciences, remote sensing-data analysis, geography, geology, and geophysics.