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: 2133699
• 负责人: Joshua Cuzzone
• 金额: $ 19.29万
• 依托单位: University of California-Los Angeles
• 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=2133699&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.

冰盖融化导致的海平面上升是未来气候变化的最大问题之一。然而，现代冰盖对气候变暖的反应到底有多大还不确定。在最后一次盛冰期，劳伦泰德冰盖覆盖了北美的大部分地区，随着气候变暖，它退缩了，这大大促进了海平面上升。现有的数据限制了过去冰盖边缘的位置和劳伦泰德冰盖冰退缩的相关时间，但对冰盖厚度知之甚少，这是冰量估计的一个关键参数。此外，冰盖在复杂地形上变薄的过程仍然不确定，这对现代冰盖的行为有直接影响。该项目将收集关于纽约阿迪朗达克山脉冰盖变薄的时间和速度的新数据，这些数据将与现有数据一起纳入一个高分辨率冰盖模型，该模型能够解决复杂地形上的冰流问题。这些新的分析将告知美国东北部劳伦泰德冰盖的表面在最后一次冰消期间如何变薄，它如何对气候做出反应，以及冰盖变薄和退缩在过去海平面上升中所起的作用。与该项目有关的教育和社区推广活动将包括向社区学院学生提供课堂和实地地质学经验和培训，该项目将收集纽约阿迪朗达克山脉更新世劳伦蒂德冰盖表面变薄的新地质年代学数据。这项研究将产生宇宙成因的表面暴露数据，这些数据将限制劳伦斯泰德冰盖内陆部分在末次冰盛期后变薄的时间和空间变异性。这些数据将与一个三维热机械冰盖模型配对，该模型能够在亚公里尺度上解析冰流。模拟将侧重于末次冰期最大期和随后的冰川终止，并将解决冰变薄，冰流和热状况的特点，在空间尺度上的地质数据提出。配对的数据模型分析解决了劳伦泰德冰盖变薄的历史，冰盖退缩的特点，以及过去的气候变化如何影响冰川消退的关键问题。该奖项反映了NSF的法定使命，并已被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。