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.

雪和冰川冰通常载有吸光颗粒。与陆冰相比，海冰表面生物地球化学在很大程度上被忽略了。原因之一是由于具有杂质的海冰的相对无法访问。这些颗粒的存在，例如黑碳和灰尘，可降低表面反照率，从而增加太阳吸收，从而迅速将杂质的冰变细。由于北极中火的频率和严重程度的增加，黑碳在北极海冰上的沉积可能正在增长。此外，融化的多年冻土可能会增加灰尘沉积到附近的海冰上。光吸收颗粒对太阳辐射的吸收增加也会增加融合水的产生和融化 - 池形成。结果，由于不安全的物理冰条件，在海冰上获得采样杂质的物理访问受到限制。该奖项支持能够从基于船只的平台起飞的综合无人机（UAS）的开发，对海冰的表面进行成像以找到理想的采样位置，并自主检索否则无法到达的雪样品。学生通过科罗拉多太空赠款财团在整个项目中订婚。 充满杂质的海冰的规模目前尚不清楚，在全球气候模型中尚未考虑。充满沉积物的冰和其他杂质对海冰生物群产生了深远的影响，可以延迟或抑制春季浮游植物和冰藻花的时机，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导致区域对北极表面能量平衡，气候和海洋初级生产力的影响，因此它也会对全球气候产生影响。杂质 - 冰反照反馈也薄薄的海冰，限制了由于不安全的冰条件而导致的物理抽样。因此，通过开发固定在UAS上的机器人采样装置以及高光谱遥感成像仪的机器人采样装置，将转换雪和冰表面生物地球化学的现场采样。有用的光谱信息的快速收集将有助于记录杂质的冰对海冰反照率的影响，机器人臂将增加基于正常无法访问的浮标的基于地面观测的空间和时间频率。这种新的综合UA将在太平洋西北和北极海洋的海冰上进行测试，并将在冰冻层的其他区域中使用广泛的应用，例如严重的缝隙冰川和冰雪。这奖反映了NSF的立法任务，并被认为是通过基金会的智力评估来评估的，并且值得通过评估来评估基金会的范围。