Collaborative Research: Assessing the timing and characteristics of deglacial Laurentide Ice Sheet thinning in the northeast United States through paired data-model analyses
Collaborative Research: Assessing the timing and characteristics of deglacial Laurentide Ice Sheet thinning in the northeast United States through paired data-model analyses
批准号:
2133699
负责人:
Joshua Cuzzone
金额:
$19.29万
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
项目状态:
未结题
起止时间:
2022-09-01 至 2025-08-31
中文摘要
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英文摘要
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.
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依托单位:
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