A paleoclimate reanalysis of the coupled Greenland Ice Sheet--climate evolution during the Last Interglacial

该项目将重建格陵兰冰盖（GrIS）在末次间冰期（127，000 - 119，000年前的温暖气候时期）的大小和形状。在这段时间里，GrIS融化了，导致海平面上升了几米，但确切的融化量尚不清楚。有必要更精确地定义这一点，因为预计GrIS在未来几年将继续融化，而这种融化将在持续的温室气体排放下加速。了解GrIS在温暖气候下对融化的敏感性可以帮助限制到2100年及以后海平面上升的程度。该项目的成果之一将是互动地图，说明GrIS在过去的样子，可用于教学和科学交流。该项目将使用一种称为数据同化的技术来实现其目标。该技术通常用于天气预报，但尚未应用于重建气候和GrIS的耦合演变。研究人员将联合收割机瞬态模拟与一个新的耦合气候-冰模型（例如，共同体地球系统模型v2与共同体冰盖模型v2），以及海洋表面温度和GrIS条件的地质代用数据（即，冰芯厚度和同位素），以产生混合模型数据产品。其结果将是对GrIS大小和形状的数据信息重建，这将允许更精确地量化GrIS对全球海平面上升的贡献。与该奖项相关的更广泛的影响包括通过地质时间创建GrIS演化的交互式可视化，支持亚利桑那大学的博士后学者和本科生，以及与南亚利桑那州研究，科学，和工程基金会，为当地的K开发气候学习和参与活动，12名学生。这一奖项反映了国家科学基金会的法定使命，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。

This project will reconstruct the size and shape of the Greenland Ice Sheet (GrIS) across the Last Interglacial period, a warm climate period 127,000-119,000 years ago. During this time, the GrIS melted substantially contributing several meters of sea level rise, but the exact amount of melting is not known. There is a need to define this more precisely because the GrIS is expected continue to melt in the coming years and this melting will accelerate under continued greenhouse gas emissions. Understanding the sensitivity of the GrIS to melting under warm climates can help constrain how much sea level rise could occur by 2100 and beyond. One outcome of this project will be interactive maps illustrating what the GrIS looked like through time, which can be used for teaching and science communication.This project will use a technique called data assimilation to achieve its goal. This technique is commonly used for weather forecasting but has not been applied yet to reconstruct the coupled evolution of climate and the GrIS. The researchers will combine transient simulations conducted with a new coupled climate-ice model (e.g., the Community Earth System Model v2 with the Community Ice Sheet Model v2) with geological proxy data for sea-surface temperature and conditions on the GrIS (i.e., ice core thickness and isotopes) in the data assimilation framework to produce a hybrid model-data product. The result will be a data-informed reconstruction of GrIS size and shape, which will allow for a more precise quantification of the contribution of the GrIS to global sea level rise. Broader Impacts associated with this award include the creation of an interactive visualization of GrIS evolution through geological time, support for a postdoctoral scholar and undergraduates at the University of Arizona, and partnership with the Southern Arizona Research, Science, and Engineering Foundation to develop climate learning and engagement activities for local K-12 students.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.