Collaborative Research: Assessing the timing and characteristics of deglacial Laurentide Ice Sheet thinning in the northeast United States through paired data-model analyses

合作研究：通过配对数据模型分析评估美国东北部冰消劳伦太德冰盖变薄的时间和特征

• 批准号: 2133698
• 负责人: Aaron Barth
• 金额: $ 27.39万
• 依托单位: Rowan University
• 依托单位国家: 美国
• 项目类别: Continuing 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=2133698&HistoricalAwards=false
• 关键词: Collaborative; Research; Assessing; timing; characteristics

Sea-level rise from melting ice sheets is one of the greatest concerns of future climate change. However, exactly how much modern ice sheets will respond to a warming climate is uncertain. During the last glacial maximum, the Laurentide Ice Sheet covered a large portion of North America, and as it retreated in response to climate warming, it contributed greatly to sea-level rise. Available data constrain the location of past ice sheet margins and associated timing of ice retreat for the Laurentide Ice Sheet, but less is known about the ice sheet thickness, a key parameter for ice-volume estimates. Furthermore, the processes by which the ice sheets thinned over complex topography remain uncertain with direct implications for modern ice-sheet behavior. This project will gather new data about the timing and rate of ice sheet thinning in the Adirondack Mountains of New York, which, together with existing data, will be incorporated into a high-resolution ice-sheet model capable of resolving ice flow across complex terrain. These new analyses will inform how the surface of the Laurentide Ice Sheet across the Northeast United States thinned during the last deglaciation, how it responded to climate, and the role this ice sheet thinning and retreat played in past sea-level rise. Educational and community outreach associated with the project will include providing in-class and field geology experience and training to community-college students.This project will gather new geochronological data of surface thinning of the Pleistocene Laurentide Ice Sheet across the Adirondack Mountains of New York. The research will generate cosmogenic surface exposure data that will constrain the timing and spatial variability of Laurentide Ice Sheet thinning after the Last Glacial Maximum for an inland sector of the ice sheet. The data will be paired with a 3-D thermomechanical ice sheet model capable of resolving ice flow at sub-kilometer scales. The simulations will focus on the Last Glacial Maximum and subsequent glacial termination and will resolve characteristics of ice thinning, ice flow, and thermal regimes at the spatial scale of the geologic data proposed. The paired data-model analysis addresses key questions of Laurentide Ice Sheet thinning histories, characteristics of ice sheet retreat, and how past climate change influenced the deglaciation.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.

融化冰盖的海平面上升是未来气候变化的最大关注点之一。但是，确切的现代冰盖对温暖气候的反应尚不确定。在最后的冰川最大值期间，劳伦德冰盖覆盖了北美的很大一部分，并且由于响应气候变暖而退缩，它为海平面上升做出了巨大贡献。可用的数据限制了过去的冰盖边缘的位置以及laurentide冰盖的冰撤退的相关时间，但对冰盖厚度的了解较少，这是冰量估计的关键参数。此外，冰盖在复杂地形上变薄的过程仍然不确定，直接对现代冰盖行为产生了直接影响。该项目将收集有关纽约阿迪朗达克山脉冰盖稀疏的时间和速率的新数据，该数据将与现有数据一起纳入能够在复杂地形上解决冰流的高分辨率冰盖模型。这些新的分析将告知美国东北部的劳伦德冰盖表面如何在上次脱气中变薄，对气候的反应以及这种冰片在过去的海平面上升中起稀疏和撤退的作用。与该项目相关的教育和社区外展活动将包括向社区校学生提供课堂和田野地质的经验和培训。该项目将收集纽约阿迪朗达克山脉更新世劳伦德赛冰原地面稀疏的新地球人工学数据。这项研究将产生宇宙性的表面暴露数据，这将限制冰盖内陆扇形最后一次冰川最大最大冰川最大值后月球冰盖的时间和空间变异性。数据将与3D热力学冰盖模型配对，该模型能够在亚公里尺度下解决冰流。模拟将集中于最后的冰川最大和随后的冰川终止，并在提出的地质数据的空间尺度上解决冰稀薄，冰流和热度状态的特征。配对的数据模型分析解决了劳伦德冰盖稀疏历史的关键问题，冰盖撤退的特征以及过去的气候变化如何影响脱水。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子优点和更广泛影响的审查标准来通过评估来通过评估来支持的。