The Antarctic Ice Sheet Large Ensemble (AISLENS) Project: Assessing the Role of Climate Variability in Past and Future Ice Sheet Mass Loss

南极冰盖大型集合体 (AISLENS) 项目：评估气候变化在过去和未来冰盖质量损失中的作用

• 批准号: 1947882
• 负责人: Alexander Robel
• 金额: $ 43.06万
• 依托单位: Georgia Tech Research Corporation
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-05-01 至 2025-04-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1947882&HistoricalAwards=false
• 关键词: Antarctic; Ice; Sheet; Large; Ensemble

Uncertainty in projections of future sea level rise comes, in part, from ice-sheet melting under the influence of unpredictable variations in ocean and atmospheric temperature near ice sheets. Using state-of-the-art modeling techniques, the Antarctic Ice Sheet Large Ensemble (AISLENS) Project will estimate the range of possible Antarctic Ice Sheet melt during the recent past and over the next several centuries that could result from such climate variations. The AISLENS Project will also facilitate research by providing modeling output as an open product to the broader climate and glaciology communities. The project will support an early career faculty member, and interdisciplinary training for a graduate student, postdoctoral fellow and undergraduate student. As a part of this project, an undergraduate course on "Sea Level Rise and Coastal Engineering" will be also developed, bringing together Earth Science and Civil Engineering students in an interdisciplinary setting and contributing to their education in sea level science and coastal adaptation. This will be done in the geographic context of the Southeastern US, the region of most concentrated vulnerability to sea-level rise in the US.The primary goal of the proposed research is to understand and quantify the role of internal climate variability in driving ice loss from the Antarctic Ice Sheet over the recent past and into the future. The AISLENS Project will encompass hundreds of simulations of Antarctic ice sheet evolution from 1950 to 2300 forced by realistic variations in climate, including snowfall and melt from fluctuating oceanic and atmospheric temperatures. Plausible realizations of Antarctic climate forcing will be generated from stochastic emulation of output from the Energy Exascale Earth System Model (E3SM) under past and future emissions scenarios. These realizations of variable climate will be used to force the MPAS Albany Land Ice (MALI) model, a state-of-the-art model of ice flow in the Antarctic Ice Sheet. In this project, AISLENS will be used to conduct uncertainty and attribution analyses. In the uncertainty analysis, the evolution of ensemble spread in simulations of the future evolution of the Antarctic Ice Sheet will be systematically decomposed to determine which temporal and spatial scales of climate variability contribute the most to future ice-sheet projection uncertainty. In the attribution analysis, a range of satellite-based observations of recent Antarctic ice loss will be compared to the envelope of internal variability of Antarctic ice loss simulated in AISLENS simulations encompassing the recent past. This analysis will provide context to recent observations indicating significant variability of Antarctic climate forcing and provide a possible path forward for conducting robust statistical inference studies for observed ice-sheet changes.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.

未来海平面上升预测的不确定性部分来自于冰盖附近海洋和大气温度不可预测的变化影响下的冰盖融化。南极冰盖大型集合体（AISLENS）项目将利用最先进的建模技术来估计由于气候变化而导致的南极冰盖在最近和未来几个世纪内可能融化的范围。 AISLENS 项目还将通过将建模输出作为开放产品提供给更广泛的气候和冰川学界来促进研究。该项目将为早期职业教员提供支持，并为研究生、博士后和本科生提供跨学科培训。作为该项目的一部分，还将开发“海平面上升和海岸工程”本科课程，将地球科学和土木工程专业的学生聚集在跨学科环境中，为他们的海平面科学和海岸适应教育做出贡献。 这项研究将在美国东南部的地理背景下进行，该地区是美国最容易受到海平面上升影响的地区。拟议研究的主要目标是了解和量化内部气候变化在驱动冰损失中的作用从最近的过去到未来的南极冰盖。 AISLENS 项目将包括对 1950 年至 2300 年南极冰盖演变的数百次模拟，这些演变是由于气候的现实变化而造成的，包括海洋和大气温度波动造成的降雪和融化。南极气候强迫的合理实现将通过对过去和未来排放情景下百亿亿次能源地球系统模型（E3SM）的输出进行随机模拟来实现。这些对气候变化的认识将用于推动 MPAS 奥尔巴尼陆地冰 (MALI) 模型的建立，这是南极冰盖冰流的最先进模型。在该项目中，AISLENS将用于进行不确定性和归因分析。在不确定性分析中，将系统地分解模拟南极冰盖未来演化中的集合扩散演化，以确定气候变化的哪些时间和空间尺度对未来冰盖预测的不确定性影响最大。在归因分析中，一系列基于卫星的近期南极冰损失观测结果将与 AISLENS 模拟中最近的南极冰损失内部变化范围进行比较。该分析将为最近的观测结果提供背景，表明南极气候强迫的显着变化，并为对观测到的冰盖变化进行稳健的统计推断研究提供可能的前进道路。该奖项反映了 NSF 的法定使命，并被认为值得通过使用评估来支持基金会的智力价值和更广泛的影响审查标准。

项目成果

Statistical Generation of Ocean Forcing With Spatiotemporal Variability for Ice Sheet Models

冰盖模型时空变化海洋强迫的统计生成

• DOI: 10.1109/mcse.2023.3300908
• 发表时间: 2023-05
• 期刊: Computing in Science & Engineering
• 影响因子: 2.1
• 作者: Muruganandham, Shivaprakash;Robel, Alexander A.;Hoffman, Matthew J.;Price, Stephen F.
• 通讯作者: Price, Stephen F.

A probabilistic framework for quantifying the role of anthropogenic climate change in marine-terminating glacier retreats

量化人为气候变化在海洋终止冰川退缩中的作用的概率框架

• DOI: 10.5194/tc-2021-394
• 发表时间: 2022-01-04
• 期刊: The Cryosphere
• 作者: J. E. Christian;A. Robel;G. Catania
• 通讯作者: G. Catania