GLOBE: The Greenland Subglacial Lake Observatory

GLOBE：格陵兰冰下湖天文台

• 批准号: EP/Y02642X/1
• 负责人: Malcolm McMillan
• 金额: $ 215.65万
• 依托单位: Lancaster University
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2024
• 资助国家: 英国
• 起止时间: 2024 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FY02642X%2F1
• 关键词: GLOBE; Greenland; Subglacial; Lake; Observatory

Theoretical predictions suggest that 1600 subglacial lakes lie hidden beneath the Greenland Ice Sheet. Yet less than 5% have been discovered to date, and studies have found only 7 that are actively filling or draining. Tracking active lakes beneath Greenland is problematic because they are 100 times smaller than those beneath Antarctica, rendering them undetectable by most standard satellite methods. Here, I will radically advance the ability to detect, monitor, forecast and understand the dynamics of active Greenland subglacial lakes at scale. GLOBE will transform the field from its current state, where almost nothing is known about their distribution, dynamics, drivers and impacts; to a position where all lakes are monitored in real time, their histories are resolved, and probabilistic forecasts predict their future drainage. GLOBE will achieve this through innovation in three key areas, 1) exploiting new, super-high resolution satellite data at scale, 2) developing new methods that exploit unconventional data, and 3) developing novel deep learning and statistical forecasting methodologies. Specifically, I will 1) use high-volume digital elevation models and machine learning to map lake activity, for the first time, over the entire continent and the past 25 years, 2) train deep learning models to search for active lakes in historical satellite imagery, 3) use video surveillance methods to autonomously identify new lake activity as it happens, and 4) use statistical techniques to make the first forecasts of future lake evolution. Ultimately, GLOBE will catalyse an entirely new approach to large-scale lake monitoring, creating a Greenland Subglacial Lake Observatory that autonomously tracks, forecasts and disseminates lake activity, thus transforming understanding of the drivers, dynamics and impacts of elusive lake drainage events.

理论上的预测表明，1600个亚冰湖隐藏在格陵兰冰盖下面。迄今为止，还没有发现不到5％的人，研究发现只有7个积极填充或排水的研究。跟踪格陵兰下的活跃湖泊是有问题的，因为它们比南极洲下方的湖泊小100倍，从而使它们无法通过大多数标准的卫星方法进行检测。在这里，我将从根本上提高检测，监视，预测和了解活跃的格陵兰冰川湖湖的动力学的能力。 Globe将从其当前状态转变该领域，那里几乎一无所知。在实时监测所有湖泊的位置，它们的历史已经解决，概率预测预测了它们的未来排水。 Globe将通过在三个关键领域的创新来实现这一目标，1）按大规模利用新的，超高的分辨率卫星数据，2）开发新的方法来利用非常规数据，3）开发新颖的深度学习和统计预测方法。 Specifically, I will 1) use high-volume digital elevation models and machine learning to map lake activity, for the first time, over the entire continent and the past 25 years, 2) train deep learning models to search for active lakes in historical satellite imagery, 3) use video surveillance methods to autonomously identify new lake activity as it happens, and 4) use statistical techniques to make the first forecasts of future lake evolution.最终，Globe将催化一种全新的大规模湖泊监测方法，从而创建一个格陵兰式冰川湖观测站，该观测站自主跟踪，预测和传播湖泊活动，从而改变了对驱动因素，动力学的理解，动态和难以捉摸的湖泊排水事件的影响。