Collaborative Research: EAR-Climate: Investigating the past, present, and future of glaciated alpine landscapes using an integrated data-model approach

合作研究：EAR-Climate：使用集成数据模型方法调查冰川高山景观的过去、现在和未来

• 批准号: 2223354
• 负责人: Leif Anderson
• 金额: $ 31.82万
• 依托单位: University of Utah
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-01 至 2025-08-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2223354&HistoricalAwards=false
• 关键词: Collaborative; Research; EAR; Climate; Investigating

Today, 80% of all glaciers are smaller than 0.5 km2, and many larger valley glaciers are in the process of transitioning to small cirque glaciers in response to modern warming. Despite their small size, cirque glaciers play an outsized geomorphic and ecological role in alpine landscapes, largely through regionally variable changes in hydrology and sediment transport. Understanding how these glaciers responded to past climate changes and how they will respond to future climate changes is prerequisite for understanding the past evolution and future fate of alpine catchments in the western U.S. and elsewhere. This project will address this need by developing detailed glaciological datasets, both modern and paleo, from an exceptionally well-constrained study site in the Teton Range, Wyoming, and integrating them with a state-of-the-art model to accurately represent glaciers as they shrink and disappear. Ultimately, this work will produce insight into the past, present, and future role of glaciers as agents of alpine landscape evolution while developing an open-source glacier model, which will be applicable to glacial settings globally. The project will also foster new collaborations between four early career PIs, improve STEM education at two public research institutions and one liberal arts college through increased participation of underrepresented minorities in the Earth sciences, and promote climate science literacy and public engagement.This research will advance our fundamental understanding of deglaciation in alpine landscapes by integrating diverse datasets into a new glacier model to simulate past and ongoing glacier retreat in the western U.S. This model represents a transformative advance in that it includes novel representation of topographically-mediated effects on mass balance—processes that are increasingly important as glaciers shrink into shaded cirques. Importantly, the new open-source glacier model (PyG2D) can be applied to other settings worldwide to quantify the effects of climate change on mountain ecosystems, hydrology, and landscapes. By applying and testing this model in the Teton Range, a site with exceptional geologic constraints on past glacier fluctuations and a suite of cirque glaciers that are representative of small glaciers globally, this project will produce the first detailed simulations of future glacier evolution in the contiguous U.S. We will place modern and future glacier change in context by constraining and simulating glacier states from the Last Ice Age to 2100 CE. This work, while focused on a single natural laboratory, has broad implications for glacierized regions elsewhere on the planet and offers an important space-for-time substitution to inform how more heavily glaciated landscapes will evolve in the future. With a continuous record of glacier extent, thickness, and volume this work will lay the foundation for future studies, both geomorphic and ecological in scope, that quantify the impact of glacier change on alpine landscapes facing complete deglaciation. Anticipated results will serve as key examples of the tangible impacts of climate change on the cryosphere that can be readily understood by resource managers, policymakers, and the broader public.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.

今天，80%的冰川小于0.5平方公里，许多较大的山谷冰川正在向小型冰斗冰川过渡，以应对现代变暖。尽管冰斗冰川的规模很小，但它们在高山景观中发挥着巨大的地貌和生态作用，主要是通过水文和沉积物输送的区域可变变化。了解这些冰川如何应对过去的气候变化，以及它们将如何应对未来的气候变化，是了解美国西部和其他地方高山集水区过去演变和未来命运的先决条件。该项目将通过从怀俄明州提顿山脉的一个非常严格的研究地点开发详细的现代和古冰川数据集，并将其与最先进的模型相结合，以准确地表示冰川收缩和消失，来满足这一需求。最终，这项工作将深入了解冰川作为高山景观演变代理人的过去，现在和未来的作用，同时开发一个开源的冰川模型，该模型将适用于全球冰川环境。该项目还将促进四个早期职业PI之间的新合作，通过增加地球科学中代表性不足的少数民族的参与，改善两个公共研究机构和一个文科学院的STEM教育，这项研究将通过将不同的数据集整合到一个新的冰川模型中来模拟过去，这个模型代表了一个变革性的进步，因为它包括地形介导的质量平衡的影响，这是越来越重要的冰川收缩成阴影的冰斗过程的新表示。重要的是，新的开源冰川模型（PyG2D）可以应用于全球其他环境，以量化气候变化对山区生态系统，水文和景观的影响。通过在提顿山脉（Teton Range）应用和测试这个模型，提顿山脉是一个对过去冰川波动有特殊地质约束的地点，也是一套代表全球小冰川的冰斗冰川，该项目将首次详细模拟美国本土未来冰川演变。我们将通过限制和模拟从末次冰期到公元2100年。这项工作虽然集中在一个单一的自然实验室，但对地球上其他地方的冰川化地区具有广泛的影响，并提供了一个重要的时空替代，以告知未来冰川化程度更高的景观将如何演变。通过对冰川范围、厚度和体积的连续记录，这项工作将为未来的地貌和生态研究奠定基础，量化冰川变化对面临完全冰川消退的高山景观的影响。预期结果将作为气候变化对冰冻圈的有形影响的关键例子，可以很容易地被资源管理者，政策制定者和更广泛的公众所理解。该奖项反映了NSF的法定使命，并被认为值得通过使用基金会的知识价值和更广泛的影响审查标准进行评估来支持。