NNA Research: The Greenland Hazards Project

航行新北极(NNA)是NSF的十大想法之一。NNA项目解决了快速变化的北极地区汇聚的科学挑战。这项北极研究需要为国家、更大区域和全球的经济、安全和韧性提供信息。NNA增强了从地方到国际的新的研究伙伴关系，使下一代北极研究人员多样化，加强正式和非正式教育的努力，并在适当的情况下整合共同创造知识。该奖项通过在以下NNA重点领域解决自然环境、社会系统和建筑环境之间的相互作用来实现这一目标的一部分：北极居民、数据和观测、教育和弹性基础设施。随着北极变暖，环境正在迅速变化；冰盖、冰帽和冰川正在变薄和消退；永久冻土正在退化。在阿拉斯加东南部和格陵兰岛等一些地区，这些变化会引发山体滑坡，当山体滑坡流入峡湾和其他沿海水域时，山体滑坡又会产生类似海啸的局部海浪。自1995年以来，几次沿海山体滑坡引发了海啸般的巨浪，悲剧性地导致格陵兰西部的生命损失、基础设施受损和社区被遗弃。该项目正在仔细绘制格陵兰如何应对冰层变薄的变化，并正在探索山体滑坡和其他灾害的发展风险。这项研究将格陵兰人在其社区中进行的当地观察与通过先进的遥感收集的数据结合在一起，以了解危险如何随着时间的推移而演变。美国和格陵兰科学家与格陵兰居民之间的合作将是确保研究满足社区需求的关键。该项目首次在格陵兰岛范围内对不稳定的土地以及灾害如何影响基础设施和社会进行了分析，同时建立了一个监测系统的原型，该系统可以为即将到来的巨浪发出警报。研究人员正在对岩崩和雪崩等高能事件进行检查和建模，以确定它们对全国各地社区的潜在海啸威胁。该项目团队假设，已知的有记录的山体滑坡分布由岩石类型、坡度和坡向控制，然后受冰川消退、永冻土变化、温度和降雨量的影响。正在使用卫星雷达、光学图像和地形差异来调查地球物理变化及其如何改变区域范围内的灾害。在地方尺度上，无人机调查正在季节性到次日的时间尺度上检查永久冻土的变化和岩石的不稳定性。机器学习和建模正在所有规模上得到应用，以确定变化的模式。此外，一项定性研究正在促进我们对沟通过程的理解，通过这些沟通过程，科学和格陵兰社区通过不同的了解方式和多种形式的专门知识赋予环境变化和危害以意义。该项目正在通过格陵兰岛的一系列讲习班建设大地测量、遥感和机器学习的能力。一个多语种网站提供了一个开放、直观、易于访问的信息来源，市政当局可以利用这些信息为决策和政策提供信息。该项目正在开发一个基于传播理论的虚拟研讨会，内容是关于NNA年度会议上的社区参与，并与NSF的项目经理分享。项目数据对许多学科都很有用，涉及固体地球地球物理、冰川学、海洋学、自然灾害和通信领域。这一奖项反映了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。

Navigating the New Arctic (NNA) is one of NSF's 10 Big Ideas. NNA projects address convergence scientific challenges in the rapidly changing Arctic. This Arctic research is needed to inform the economy, security and resilience of the Nation, the larger region, and the globe. NNA empowers new research partnerships from local to international scales, diversifies the next generation of Arctic researchers, enhances efforts in formal and informal education, and integrates the co-production of knowledge where appropriate. This award fulfills part of that aim by addressing interactions among the natural environment, social systems, and the built environment in the following NNA focus areas: Arctic Residents, Data and Observation, Education, and Resilient Infrastructure.As the Arctic warms, the environment is rapidly changing; ice sheets, ice caps, and glaciers are thinning and receding; and permafrost is degrading. In some areas, such as southeastern Alaska and Greenland, these changes can trigger landslides, which in turn can generate localized tsunami-like waves when the landslides flow into fjords and other coastal waters. Since 1995, several coastal landslides have triggered tsunami-like waves, tragically resulting in the loss of lives, damage to infrastructure, and the abandonment of communities in western Greenland. This project is carefully mapping how Greenland is changing in response to ice thinning and is exploring the developing risk of landslides and other hazards. The research integrates local observations made by Greenlandic people in their communities with data collected through advanced remote sensing to learn how hazards evolve over time. The collaboration between US and Greenlandic scientists and Greenlandic residents will be critical to ensure that the research addresses community needs. This project is providing the first Greenland-wide analysis of unstable land and how hazards affect infrastructure and society, while prototyping a monitoring system that could provide warning of approaching large waves. Researchers are examining and modeling high energy events such as rockslides and avalanches to ascertain their potential tsunami threats to communities around the country. The project team hypothesizes that the known distribution of recorded landslides is controlled by rock type, slope and aspect and then by proximity to retreating glaciers, changing permafrost, temperatures and precipitation. Satellite radar, optical imagery and topographic differencing are being used to investigate geophysical changes and how they alter hazards on regional scales. On local scales, drone surveys are examining permafrost changes and rock instabilities on seasonal to sub-daily timescales. Machine learning and modeling are being applied at all scales to identify patterns of change. In addition, a qualitative study is advancing our understanding of the communication processes through which scientific and Greenlandic communities give meaning to environmental changes and hazards through diverse ways of knowing and multiple forms of expertise. The project is building capacity for geodesy, remote sensing, and machine learning through a series of workshops in Greenland. A multilingual website is providing a source of open, intuitively understandable, and easily accessible information that municipalities can use to inform decision making and policy. The project is developing a communication-theory based virtual workshop on community engagement at annual NNA meetings that is being shared with program managers at NSF. The project data are useful to a wide range of disciplines, with work relevant to solid earth geophysics, glaciology, oceanography, natural hazards, and the field of communication.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.