Glacier Calving-observations and Modelling

冰川崩解-观测和建模

• 批准号: 2743624
• 金额: --
• 依托单位: Northumbria University
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2022
• 资助国家: 英国
• 起止时间: 2022 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2743624
• 关键词: Glacier; Calving; observations; Modelling

Glacier calving is the process of ice loss through the breaking of ice from the edge of a glacier. Ice-flow models describe calving in a number of different ways, and there is still no consensus on the best approach. Recent work suggests that calving can give rise to an unstable run-away process and some of the higher-end predictions of near-future global sea level rely on models implementing such an unstable frontal retreat. In this project, both observational and numerical methods are used to better understand the calving process and how best to implement calving numerically. The aim is to arrive at a description that results in good agreement with observations, while at the same time being numerically robust and flexible enough to fit into an existing modelling framework used in large-scale ice-sheet modelling today. Of particular interest is the possibility of some types of calving-laws giving rise to an unstable retreat. This idea will be investigated and tested using numerical ice-flow models and simplified analytical models. Observational data will be primarily based on remote sensing data from Greenland, Iceland and Antarctica with additional new data sets to be collected from lake-terminating glaciers in Iceland. The near-future evolution of Pine-Island glacier, Antarctica, will be modelled using different types of calving laws, and the importance of calving formulations assess through formal uncertainty-quantification methodology. The work will be tightly integrated with existing international research projects and other groups currently working on similar problems. The student will benefit and contribute to work conduced at Northumbria University as a part of the NSFPLR-NERC funded project: Processes, drivers, predictions: Modeling the response of Thwaites Glacier over the next century using ice/ocean coupled models.

冰川崩解是冰川边缘的冰破裂导致冰损失的过程。冰流模型以多种不同的方式描述冰崩解，但对于最佳方法仍没有达成共识。最近的研究表明，崩解可能会导致不稳定的失控过程，并且对近期全球海平面的一些高端预测依赖于实施这种不稳定的锋面撤退的模型。在该项目中，使用观察和数值方法来更好地了解产犊过程以及如何最好地以数值方式实施产犊。目的是获得一种与观测结果吻合良好的描述，同时具有足够的数值鲁棒性和灵活性，以适应当今大规模冰盖建模中使用的现有建模框架。特别令人感兴趣的是某些类型的产犊法则可能导致不稳定的撤退。将使用数值冰流模型和简化分析模型对这一想法进行研究和测试。观测数据将主要基于格陵兰岛、冰岛和南极洲的遥感数据，并从冰岛的湖泊终止冰川收集额外的新数据集。南极洲松岛冰川近期的演化将使用不同类型的崩解法则进行建模，并通过正式的不确定性量化方法评估崩解公式的重要性。这项工作将与现有的国际研究项目和目前研究类似问题的其他小组紧密结合。该学生将受益于诺森比亚大学进行的工作，作为 NSFPLR-NERC 资助项目的一部分：过程、驱动因素、预测：使用冰/海洋耦合模型对思韦茨冰川在下个世纪的响应进行建模。