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)的大小和形状，横跨最后一次间冰期，即12.7万-11.9万年前的温暖气候时期。在此期间，格雷火山融化，导致海平面上升了几米，但确切的融化量尚不清楚。有必要更准确地定义这一点，因为预计在未来几年，全球资源融化指数将继续融化，而在温室气体持续排放的情况下，这种融化将会加速。了解GRI对温暖气候下融化的敏感性，有助于限制到2100年及以后海平面可能上升的幅度。这个项目的一个成果将是交互式地图，它展示了地球资源信息系统随着时间的推移是什么样子的，可用于教学和科学交流。该项目将使用一种名为数据同化的技术来实现其目标。这项技术通常用于天气预报，但尚未被应用于重建气候和GRIS的耦合演变。研究人员将把利用新的气候-冰耦合模式(例如，共同体地球系统模式v2和共同体冰盖模式v2)进行的瞬变模拟与数据同化框架中海表面温度和GRI条件(即冰芯厚度和同位素)的地质替代数据结合起来，以产生一个混合模式-数据产品。其结果将是在数据基础上重建全球海平面上升指数的大小和形状，从而能够更准确地量化全球海平面上升的影响。与该奖项相关的更广泛的影响包括创建地质时间中GRIS演化的交互式可视化，支持亚利桑那大学的一名博士后学者和本科生，以及与南亚利桑那州研究、科学和工程基金会合作，为当地K-12学生开发气候学习和参与活动。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

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.