EAGER: Collaborative Research: Autonomous retrieval of impurity-laden Arctic sea ice and hyperspectral surface properties through innovative robotics

EAGER：合作研究：通过创新机器人技术自主检索充满杂质的北极海冰和高光谱表面特性

• 批准号: 2218834
• 负责人: Alia Khan
• 金额: $ 23.69万
• 依托单位: Western Washington University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-05-01 至 2025-04-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2218834&HistoricalAwards=false
• 关键词: EAGER; Collaborative; Research; Autonomous; retrieval

Snow and glacier ice are often laden with light absorbing particles. By comparison to land ice, sea ice surface biogeochemistry has been largely ignored. One reason is due to the relative inaccessibility of impurity-laden sea ice. The presence of these particles, such as black carbon and dust, lowers the surface albedo, resulting in increased solar absorption that quickly thins the impurity-laden ice. Deposition of black carbon onto Arctic sea ice is likely growing due to the increasing frequency and severity of fires in the Arctic. Additionally, thawing permafrost may be increasing dust deposition onto nearby sea ice. The increased absorption of solar radiation by the light absorbing particles also increases meltwater generation and melt-pond formation. As a result, physical access to sampling impurities on sea ice is limited due to unsafe physical ice conditions. This award supports development of an integrated unmanned aerial system (UAS) capable of taking off from a ship-based platform, imaging the surface of the sea ice to locate ideal sampling locations, and autonomously retrieving snow samples that would otherwise be unreachable. Students are engaged throughout this project via the Colorado Space Grant Consortium. The scale of impurity-laden sea ice is currently unknown and is not accounted for in global climate models. Sediment-laden ice and other impurities have a profound impact on sea ice biota and can delay or inhibit the timing of the spring phytoplankton and ice algae bloom, thereby impacting the entire marine ecosystem. Given that these localized albedo responses and feedbacks lead to regional impacts on the Arctic surface energy balance, climate, and ocean primary productivity, it will have repercussions for the global climate as well. The impurity-ice albedo feedbacks also thin the sea ice, limiting physical sampling due to unsafe ice conditions. Therefore, field sampling of snow and ice surface biogeochemistry will be transformed by developing a robotic sampling device affixed to an UAS, together with a hyperspectral remote sensing imager. The rapid collection of useful spectral information will help document the impact impurity-laden ice has on sea ice albedo and the robotic arm will increase the spatial and temporal frequency of ground-based observations from normally inaccessible floes. This new integrated UAS will be tested in the Pacific Northwest and on sea ice in the Arctic Ocean and will have broad applications for use in other regions of the cryosphere, such as heavily crevassed glaciers and ice sheets.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.

雪和冰川通常充满光吸收颗粒。与陆地冰相比，海冰表面的生物地球化学在很大程度上被忽视了。原因之一是由于富含杂质的海冰相对难以接近。这些颗粒（例如黑碳和灰尘）的存在会降低表面反照率，导致太阳吸收增加，从而迅速使充满杂质的冰变薄。由于北极火灾的频率和严重程度不断增加，北极海冰上的黑碳沉积可能会增加。此外，永久冻土的融化可能会增加附近海冰上的灰尘沉积。光吸收颗粒对太阳辐射的吸收增加也增加了融水的产生和融水池的形成。因此，由于不安全的物理冰条件，物理获取海冰上杂质的采样受到限制。该奖项支持开发一种集成无人机系统（UAS），该系统能够从船基平台起飞，对海冰表面进行成像以定位理想的采样位置，并自动检索原本无法到达的雪样本。学生通过科罗拉多太空资助联盟参与整个项目。 充满杂质的海冰的规模目前尚不清楚，也没有在全球气候模型中得到考虑。富含沉积物的冰和其他杂质对海冰生物群产生深远的影响，可以延迟或抑制春季浮游植物和冰藻繁殖的时间，从而影响整个海洋生态系统。鉴于这些局部反照率响应和反馈会对北极表面能量平衡、气候和海洋初级生产力产生区域影响，它也会对全球气候产生影响。杂质冰反照率反馈也会使海冰变薄，由于不安全的冰况而限制了物理采样。因此，通过开发固定在无人机上的机器人采样装置以及高光谱遥感成像仪，将改变雪和冰表面生物地球化学的现场采样。快速收集有用的光谱信息将有助于记录富含杂质的冰对海冰反照率的影响，而机械臂将增加对通常无法到达的浮冰进行地面观测的空间和时间频率。这种新型综合无人机系统将在太平洋西北地区和北冰洋海冰上进行测试，并将在冰冻圈的其他区域（例如严重裂隙的冰川和冰盖）具有广泛的应用。该奖项反映了 NSF 的法定使命，并已通过使用基金会的智力优点和更广泛的影响审查标准进行评估，被认为值得支持。