NSF-NERC: PROcesses, drivers, Predictions: Modeling the response of Thwaites Glacier over the next Century using Ice/Ocean Coupled Models (PROPHET)

NSF-NERC：过程、驱动因素、预测：使用冰/海洋耦合模型 (PROPHET) 模拟思韦茨冰川在下个世纪的响应

• 批准号: 2152622
• 负责人: Mathieu Morlighem
• 金额: $ 111.95万
• 依托单位: Dartmouth College
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-08-15 至 2025-03-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2152622&HistoricalAwards=false
• 关键词: NSF; NERC; PROcesses; drivers; Predictions

This project contributes to the joint initiative launched by the U.S. National Science Foundation (NSF) and the U.K. Natural Environment Research Council (NERC) to substantially improve decadal and longer-term projections of ice loss and sea-level rise originating from Thwaites Glacier in West Antarctica. Thwaites Glacier has been accelerating and widening over the past three decades. How fast Thwaites will disintegrate or how quickly it will find a new stable state have become some of the most important questions of the future of the West Antarctic Ice Sheet and its contribution to sea-level rise over the next decades to centuries and beyond. This project will rely on three independent numerical models of ice flow, coupled to an ocean circulation model to (1) improve our understanding of the interactions between the ice and the underlying bedrock, (2) analyze how sensitive the glacier is to external changes, (3) assess the processes that may lead to a collapse of Thwaites, and, most importantly, (4) forecast future ice loss of Thwaites. By providing predictions based on a suite of coupled ice-ocean models, this project will also assess the uncertainty in model projections.The project will use three independent ice-sheet models: Ice Sheet System Model, Ua, and STREAMICE, coupled to the ocean circulation model of the MIT General Circulation Model. The team will first focus on the representation of key physical processes of calving, ice damage, and basal slipperiness that have either not been included, or are poorly represented, in previous ice-flow modelling work. The team will then quantify the relative role of different proposed external drivers of change (e.g., ocean-induced ice-shelf thinning, loss of ice-shelf pinning points) and explore the stability regime of Thwaites Glacier with the aim of identifying internal thresholds separating stable and unstable grounding-line retreat. Using inverse methodology, the project will produce new physically consistent high-resolution (300-m) data sets on ice-thicknesses from available radar measurements. Furthermore, the team will generate new remote sensing data sets on ice velocities and rates of elevation change. These will be used to constrain and validate the numerical models, and will also be valuable stand-alone data sets. This process will allow the numerical models to be constrained more tightly by data than has previously been possible. The resultant more robust model predictions of near-future impact of Thwaites Glacier on global sea levels can inform policy-relevant decision-making.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该项目为美国国家科学基金会 (NSF) 和英国自然环境研究委员会 (NERC) 发起的联合倡议做出了贡献，该倡议旨在大幅改进对源自西部思韦茨冰川的冰损失和海平面上升的十年和长期预测南极洲。 过去三十年来，思韦茨冰川一直在加速扩张。思韦茨冰盖解体的速度有多快，或者它能以多快的速度找到新的稳定状态，已经成为有关西南极冰盖未来及其对未来几十年到几个世纪甚至更长时间内海平面上升的贡献的一些最重要的问题。 该项目将依赖于三个独立的冰流数值模型，与海洋环流模型相结合，以（1）提高我们对冰与底层基岩之间相互作用的理解，（2）分析冰川对外部变化的敏感程度， （3）评估可能导致思韦茨塌陷的过程，最重要的是，（4）预测思韦茨未来的冰损失。通过提供基于一套耦合冰海模型的预测，该项目还将评估模型预测的不确定性。该项目将使用三个独立的冰盖模型：冰盖系统模型、Ua 和 STREAMICE，与海洋耦合麻省理工学院大气循环模型的循环模型。该团队将首先关注崩解、冰损伤和基底滑移等关键物理过程的表示，这些过程在之前的冰流建模工作中要么没有包含在内，要么表现不佳。然后，该团队将量化不同提议的外部变化驱动因素（例如，海洋引起的冰架变薄、冰架固定点的丧失）的相对作用，并探索思韦茨冰川的稳定状态，目的是确定分离冰架的内部阈值。稳定接地线退避和不稳定接地线退避。 该项目将使用逆向方法，从可用的雷达测量中产生新的物理一致的高分辨率（300米）冰厚数据集。 此外，该团队还将生成有关冰速度和海拔变化率的新遥感数据集。这些将用于约束和验证数值模型，并且也将是有价值的独立数据集。这一过程将使数值模型比以前更严格地受到数据的约束。 由此产生的对思韦茨冰川近期对全球海平面影响的更稳健的模型预测可以为政策相关决策提供信息。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响进行评估，被认为值得支持审查标准。

项目成果

Model insights into bed control on retreat of Thwaites Glacier, West Antarctica

对西南极洲思韦茨冰川退缩过程中河床控制的模型分析

• DOI: 10.1017/jog.2023.13
• 发表时间: 2023-10
• 期刊: Journal of Glaciology
• 影响因子: 3.4
• 作者: Schwans, Emily;Parizek, Byron R.;Alley, Richard B.;Anandakrishnan, Sridhar;Morlighem, Mathieu M.
• 通讯作者: Morlighem, Mathieu M.

Recrystallization of ice enhances the creep and vulnerability to fracture of ice shelves

冰的再结晶增强了冰架的蠕变和断裂脆弱性

• DOI: 10.1016/j.epsl.2021.117219
• 发表时间: 2021-12
• 期刊: Earth and Planetary Science Letters
• 影响因子: 5.3
• 作者: Ranganathan, Meghana;Minchew, Brent;Meyer, Colin R.;Peč, Matěj
• 通讯作者: Peč, Matěj

Assessment of numerical schemes for transient, finite-element ice flow models using ISSM v4.18

使用 ISSM v4.18 评估瞬态有限元冰流模型的数值方案

• DOI: 10.5194/gmd-14-2545-2021
• 发表时间: 2021-01
• 期刊: Geoscientific Model Development
• 影响因子: 5.1
• 作者: dos Santos, Thiago Dias;Morlighem, Mathieu;Seroussi, Hélène
• 通讯作者: Seroussi, Hélène

A new vertically integrated MOno-Layer Higher-Order (MOLHO) ice flow model

一种新的垂直集成单层高阶 (MOLHO) 冰流模型

• DOI: 10.5194/tc-16-179-2022
• 发表时间: 2022-01
• 期刊: The Cryosphere
• 作者: Dias dos Santos, Thiago;Morlighem, Mathieu;Brinkerhoff, Douglas
• 通讯作者: Brinkerhoff, Douglas

Data‐Driven Inference of the Mechanics of Slip Along Glacier Beds Using Physics‐Informed Neural Networks: Case Study on Rutford Ice Stream, Antarctica

使用物理学数据驱动的沿冰川床滑动力学的推断——知情神经网络：南极洲拉特福德冰流案例研究

• DOI: 10.1029/2021ms002621
• 发表时间: 2021-09-23
• 期刊: Journal of Advances in Modeling Earth Systems
• 影响因子: 6.8
• 作者: B. Riel;B. Minchew;T. Bischoff
• 通讯作者: T. Bischoff