Results, Code and Data for Quantitative Assessment of Stabilizing or Destabilizing Effect of Fjord Geometry on Greenland Tidewater Glaciers 1985-2020

To download and unzip this dataset, manually download the file a00_download_arcticdata.py, and then run using Python3: python a00_download_arcticdata.py ~/download_location 3 NOTE: You may have to authenticate and set the TOKEN environment variable, see the "Authentication" section of: https://arcticdata.io/catalog/api This study systematically examines the stress state of Greenland tidewater glaciers based on available surface velocities, terminus positions, ice thickness and bed elevations. The von Mises Calving Law is used to assess the contributions of fjord geometry to a glacier’s stability, or lack thereof. If a glacier’s expected calving rate increases upon terminus retreat after taking into account the empirical ocean heating relationship of, then fjord geometry contributes to instability; whereas a decrease signals a stabilizing fjord contribution. This principle is used to systematically evaluate 44 Greenland tidewater glaciers. Of those glaciers, 13 were found to have fjord geometry that currently contributes to instability; 7 with stabilizing geometry; and 24 that lacked statistical significance. Although the methodology as it currently stands is able to provide insight on a variety of already-retreating glaciers, it is only able to analyze terminus positions that have already been realized in the past. Therefore, it is unable to provide insight on historically stable glaciers, or on future terminus positions for which fjord geometry might change from stabilizing to destabilizing or vice versa. Future studies involving dynamic ice models could use the methodology presented here to address those questions. Full per-glaciers results are included. Python code to download external datasets, process / plot results and repeat this study is included, along with all datasets generated by this study.若需下载并解压本数据集，请手动获取a00_download_arcticdata.py文件，随后通过Python3运行如下命令：python a00_download_arcticdata.py ~/download_location 3。注意：您可能需要完成身份验证并配置TOKEN环境变量，详情请参阅https://arcticdata.io/catalog/api的"Authentication"章节。本研究基于现有地表流速、冰舌位置、冰厚及床面高程数据，系统分析了格陵兰潮汐冰川的应力状态。本研究采用冯·米塞斯崩解法则（von Mises Calving Law），评估峡湾几何形态对冰川稳定性的影响（或反之）。若在纳入经验海洋热关系后，冰川因冰舌退缩导致预期崩解速率上升，则峡湾几何形态会加剧冰川不稳定性；反之，若崩解速率下降，则表明峡湾几何形态起到稳定作用。基于该原理，本研究系统评估了44条格陵兰潮汐冰川。结果显示，其中13条冰川的峡湾几何形态当前会加剧不稳定性，7条具备稳定作用，剩余24条则无统计学显著性。尽管当前方法可对已发生退缩的冰川开展分析，但仅能基于历史已观测到的冰舌位置进行研究。因此，该方法无法针对历史上保持稳定的冰川，或是峡湾几何形态可能从稳定转为不稳定（反之亦然）的未来冰舌位置提供相关见解。后续可结合动态冰流模型，采用本文提出的方法解决上述问题。本研究附带全部单冰川结果、用于下载外部数据集、处理并绘制结果可视化图表以及复现本研究的Python代码，以及本研究生成的所有数据集。