CONNECTing past, present and future: hindcast and forecast of Antarctic ice loss between 1990 and 2100

连接过去、现在和未来：1990 年至 2100 年间南极冰损失的事后预测和预测

• 批准号: MR/W011816/1
• 负责人: Jan De Rydt
• 金额: $ 157.22万
• 依托单位: Northumbria University
• 依托单位国家: 英国
• 项目类别: Fellowship
• 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=MR%2FW011816%2F1
• 关键词: CONNECTing; past; present; future; hindcast

Satellite observations provide glaciologists with increasingly complete and frequent maps of ice velocity and thickness changes of the Antarctic Ice Sheet (AIS). For nearly three decades, satellites have helped us identify the physical processes that underlie contemporary rates of mass loss from the AIS, and have been key in quantifying Antarctica's present-day contribution to global sea level rise. However, the fundamental issue remains how these changes will evolve in a warming world, and what their global impact will be on sea level, climate and ecosystems. In order to provide reliable forecasts of ice sheet changes, and CONNECT the past, present and future, we need validated models with robust uncertainty quantification. This is what this project offers. In parallel with the satellite revolution, ice sheet models have advanced significantly over the last decade. Confidence in their ability to produce numerically robust projections for complex geometries and 'external' forcing has greatly improved, and essential dynamical interactions with the ocean and atmosphere can now be included. Yet, no systematic attempt has been made at comparing hindcasts of past changes from modern ice flow models with the rich, 30-year repository of satellite data from Antarctica. A model validation exercise of this type is both timely and critical: it needs the long time series of observations and sophisticated models that are now available, and it forms a prerequisite for reliable forecasts of the AIS's impact on global sea levels in the 21st century. In light of this important deficiency in ice sheet modelling and the need for robust, century-scale forecasts, De Rydt and his team of PDRAs and international project partners will address three distinct challenges: (1) the initial value problem of predicting the evolution of the Ice Sheet given an uncertain estimate of its present-day state, (2) the structural problem of unknown/uncertain physical parameters, and (3) the boundary value problem of assessing future changes in the state of the Ice Sheet due to uncertain future climate forcing.Building on De Rydt's internationally recognised expertise in ice dynamics and ice-ocean modelling, the team will first generate a best estimate of the state of the AIS in the 1990s through data assimilation in a coupled ice-ocean model, and perform the first circumpolar Bayesian uncertainty analysis to quantify how errors in the initial conditions are amplified by forward integration with realistic forcing between 1990 and 2020. Next, they will use newly developed techniques in perturbed physics ensembles in combination with model emulators to systematically sample uncertain model physics (basal sliding, ice rheology, calving, etc) and assess their impact on forecasts within a probabilistic framework. This will allow them to comprehensively validate a next-generation coupled ice-ocean model for the first time and identify the physical parameter space that is consistent with observations. Finally, they will use output from a range of global climate simulations in combination with perturbed physics ensembles to obtain an improved estimate of ice loss from the AIS between now and 2100, with a robust quantification of all model errors and consistent with the observational record. The project will foster international collaboration, bring significant advances in the field with broader societal impact, and establish the PI and his team as world-leaders in the field. Key findings will be published in high impact scientific journals and contribute to future IPCC reports. Through partnerships with NUSTEM and the International Glaciology Society and through project websites, public lectures, school workshops and social media channels, the team will communicate about the wider societal and environmental aspects of sea level rise with key stakeholders in climate policy, young people and their influencers in North East England, and a worldwide audience.

卫星观测为冰川学家提供了越来越完整和频繁的南极冰盖（AIS）冰速和厚度变化图。近三十年来，卫星帮助我们确定了AIS当代质量损失率的物理过程，并在量化南极洲对全球海平面上升的贡献方面发挥了关键作用。然而，根本问题仍然是这些变化将如何在变暖的世界中演变，以及它们对海平面、气候和生态系统的全球影响。为了提供可靠的冰盖变化预测，并预测过去，现在和未来，我们需要验证模型与强大的不确定性量化。这就是这个项目所提供的。在卫星革命的同时，冰盖模型在过去十年中取得了重大进展。人们对他们针对复杂几何形状和“外部”强迫进行数值稳健预测的能力的信心大大提高，现在可以包括与海洋和大气的基本动力相互作用。然而，还没有系统地尝试将现代冰流模型对过去变化的后报与南极洲30年来丰富的卫星数据库进行比较。这种类型的模型验证工作既及时又关键：它需要长时间序列的观测和现有的复杂模型，它是可靠预测AIS对21世纪全球海平面影响的先决条件。鉴于冰盖建模的这一重要缺陷以及对强大的世纪规模预测的需求，De Rydt和他的PDRA团队以及国际项目合作伙伴将解决三个不同的挑战：（1）在对冰盖当前状态给出不确定估计的情况下，预测冰盖演变的初值问题，（2）未知/不确定物理参数的结构问题，以及（3）由于不确定的未来气候强迫，评估冰盖状态未来变化的边界值问题。基于De Rydt在冰动力学和冰-海模型方面的国际公认的专业知识，该团队将首先通过冰-海耦合模型中的数据同化，并执行第一次绕极贝叶斯不确定性分析，以量化1990年至2020年期间初始条件中的误差是如何通过实际强迫的前向积分放大的。接下来，他们将使用新开发的扰动物理集合技术与模型仿真器相结合，系统地对不确定的模型物理（基底滑动，冰流变学，产犊等）进行采样，并在概率框架内评估其对预测的影响。这将使他们能够首次全面验证下一代冰-海耦合模型，并确定与观测结果一致的物理参数空间。最后，他们将使用一系列全球气候模拟的输出，结合扰动物理集合，以获得从现在到2100年AIS冰损失的改进估计，并对所有模型误差进行稳健的量化，并与观测记录保持一致。该项目将促进国际合作，在该领域取得重大进展，产生更广泛的社会影响，并使PI及其团队成为该领域的世界领导者。主要研究结果将发表在高影响力的科学期刊上，并为未来的IPCC报告做出贡献。通过与NUSTEM和国际冰川学会的合作，并通过项目网站，公开讲座，学校研讨会和社交媒体渠道，该团队将与气候政策的主要利益相关者，英格兰东北部的年轻人及其影响者以及全球观众交流海平面上升的更广泛的社会和环境方面。

项目成果

Unavoidable future increase in West Antarctic ice-shelf melting over the twenty-first century

二十一世纪南极西部冰架融化的未来不可避免的增加

• DOI: 10.1038/s41558-023-01818-x
• 发表时间: 2023
• 期刊: Nature Climate Change
• 影响因子: 30.7
• 作者: Naughten K

Recent irreversible retreat phase of Pine Island Glacier

松岛冰川近期不可逆转的退缩阶段

• DOI: 10.1038/s41558-023-01887-y
• 发表时间: 2023
• 期刊: Nature Climate Change
• 影响因子: 30.7
• 作者: Reed B

Short- and long-term variability of the Antarctic and Greenland ice sheets

• DOI: 10.1038/s43017-023-00509-7
• 发表时间: 2024-02
• 期刊: Nature Reviews Earth & Environment
• 作者: Edward Hanna;Dániel Topál;J. Box;S. Buzzard;Frazer D. W. Christie;Christine Hvidberg;M. Morlighem