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

这项研究项目将汇集几年来对阿拉斯加BBGS冰川系统涌浪的观测结果和有限元模型实验的结果，以加强对复杂冰川系统在涌浪过程中动态过程的了解。阿拉斯加的白令-巴格利冰川系统是地球上最大的涌浪型冰川，也是格陵兰和南极冰盖以外最大的冰川系统。项目成果将增加对阿拉斯加冰川加速过程和格陵兰冰盖出口冰川过程的了解，从而有助于减少海平面上升预测的不确定性。该项目将为一名研究生和三名来自跨学科和不同背景的本科生提供教育和培训机会。该项目还将开发供阿拉斯加和科罗拉多州高中直接使用的教育单元，并为其他地方的学校建立一个网络课程单元，重点关注白令冰川激增和一般的激增现象。了解快速流动的冰川和冰流的加速对于了解冰冻圈的变化以及海平面的变化至关重要。在当前气候变暖领域，冰川加速是评估海平面上升的主要不确定性来源。涌动是最少的--对四种冰川加速作用的研究。因为它们突然以准周期和不可预测的方式加速和前进，汹涌的冰川与冰冻圈中似乎无处不在的退缩形成了反差。目前白令-巴格利冰川系统的激增为观察和分析大型复杂冰川系统的激增提供了难得的机会。该项目将包括观测、数据分析、数据参数化以及数据分析和基于模型的数值实验结果的比较。调查人员将分析研究团队在几年的空中活动中收集的数据，以及来自NASA、欧洲航天局和商业卫星的机载和卫星激光高度计和图像数据，以及冰下地形的雷达数据。研究人员继续努力将地球观测、遥感和数值模拟结合在一起。他们将应用他们之前开发的自动分类系统，从裂缝区域的图像中识别物理参数。冰流在典型的不同阶段的冰流的快速变化，通常持续数年，尽管具有不同的地区减缓和加速，在复杂的裂缝模式中表现得很明显。推导出的物理参数直接与变形和其他冰动力学变量有关，这些变量很难用其他方法提取，但对于物理建模是必要的。基于图像的分类方法预计将普遍适用于环境和空间科学、遥感数据分析、地理、地质和地球物理等其他领域。

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.