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

基本信息

  • 批准号:
    2218835
  • 负责人:
  • 金额:
    $ 6.31万
  • 依托单位:
  • 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

项目摘要

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.
雪和冰川冰通常充满了光吸收颗粒。与陆地冰相比,海冰表面的地球化学在很大程度上被忽视了。一个原因是由于相对难以接近的杂质负载海冰。这些颗粒的存在,如炭黑和灰尘,降低了表面的辐射,导致太阳能吸收增加,迅速使充满杂质的冰变薄。由于北极地区火灾的频率和严重程度越来越高,黑碳在北极海冰上的沉积可能会增加。此外,融化的永久冻土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增加的吸收也增加了融水的产生和融池的形成。因此,由于不安全的物理冰条件,对海冰上的杂质进行采样的物理访问受到限制。该奖项支持开发一种集成的无人机系统(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,并自主检索否则无法获取的雪样。学生们通过科罗拉多空间赠款财团参与整个项目。 目前尚不清楚载有杂质的海冰的规模,也没有在全球气候模型中考虑到。载有沉积物的冰和其他杂质对海冰生物群有着深远的影响,可以延迟或抑制春季浮游植物和冰藻水华的时间,从而影响整个海洋生态系统。鉴于这些局部的北极涛动响应和反馈导致对北极地表能量平衡、气候和海洋初级生产力的区域性影响,它也将对全球气候产生影响。杂质冰的反作用也使海冰变薄,由于不安全的冰况,限制了物理采样。因此,将通过开发一种固定在无人机上的机器人采样装置以及一台高光谱遥感成像仪,改变冰雪表面地球化学的实地采样。快速收集有用的光谱信息将有助于记录载有杂质的冰对海冰的影响,机械臂将增加从通常无法进入的浮冰进行地面观测的空间和时间频率。这一新的综合无人机系统将在太平洋西北部和北冰洋的海冰上进行测试,并将在冰冻圈的其他区域(如严重裂缝的冰川和冰盖)中得到广泛应用。该奖项反映了NSF的法定使命,并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,被认为值得支持。

项目成果

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Julienne Stroeve其他文献

Sea level trends along the South African coast from 1993 to 2022 using XTRACK altimetry, tide gauges, and GNSS measurements
使用 XTRACK 测高仪、验潮仪和全球导航卫星系统测量的 1993 年至 2022 年南非沿海海平面趋势
  • DOI:
    10.1038/s41598-025-89258-9
  • 发表时间:
    2025-02-10
  • 期刊:
  • 影响因子:
    3.900
  • 作者:
    Franck Eitel Kemgang Ghomsi;Muharrem Hilmi Erkoç;Roshin P. Raj;Atinç Pirti;Antonio Bonaduce;Babatunde J. Abiodun;Julienne Stroeve
  • 通讯作者:
    Julienne Stroeve
Mapping of sea ice in 1975 and 1976 using the NIMBUS-6 Scanning Microwave Spectrometer (SCAMS)
1975年和1976年使用雨云 - 6号扫描微波光谱仪(SCAMS)对海冰进行的测绘
  • DOI:
    10.1016/j.rse.2025.114815
  • 发表时间:
    2025-10-01
  • 期刊:
  • 影响因子:
    11.400
  • 作者:
    Wiebke Margitta Kolbe;Rasmus T. Tonboe;Julienne Stroeve
  • 通讯作者:
    Julienne Stroeve
Enhanced sea ice classification for ICESat-2 using combined unsupervised and supervised machine learning
利用无监督和有监督机器学习相结合的方法提升ICESat-2卫星数据的海冰分类能力
  • DOI:
    10.1016/j.rse.2025.114607
  • 发表时间:
    2025-03-01
  • 期刊:
  • 影响因子:
    11.400
  • 作者:
    Wenxuan Liu;Michel Tsamados;Alek Petty;Taoyong Jin;Weibin Chen;Julienne Stroeve
  • 通讯作者:
    Julienne Stroeve
Mapping of sea ice concentration using the NASA NIMBUS 5 Electrically Scanning Microwave Radiometer data from 1972–1977
使用 1972 年至 1977 年 NASA NIMBUS 5 电扫描微波辐射计数据绘制海冰浓度图
  • DOI:
    10.5194/essd-16-1247-2024
  • 发表时间:
    2024
  • 期刊:
  • 影响因子:
    11.4
  • 作者:
    Wiebke M. Kolbe;R. Tonboe;Julienne Stroeve
  • 通讯作者:
    Julienne Stroeve
Long-term prediction of Arctic sea ice concentrations using deep learning: Effects of surface temperature, radiation, and wind conditions
  • DOI:
    10.1016/j.rse.2024.114568
  • 发表时间:
    2025-03-01
  • 期刊:
  • 影响因子:
  • 作者:
    Young Jun Kim;Hyun-cheol Kim;Daehyeon Han;Julienne Stroeve;Jungho Im
  • 通讯作者:
    Jungho Im

Julienne Stroeve的其他文献

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{{ truncateString('Julienne Stroeve', 18)}}的其他基金

DEFIANT: Drivers and Effects of Fluctuations in sea Ice in the ANTarctic
挑战:南极海冰波动的驱动因素和影响
  • 批准号:
    NE/W004712/1
  • 财政年份:
    2021
  • 资助金额:
    $ 6.31万
  • 项目类别:
    Research Grant
Seasonal evolution of Ku- and Ka-band backscattering horizon over snow on first-year and multiyear sea ice
第一年和多年海冰雪上 Ku 和 Ka 波段后向散射地平线的季节演变
  • 批准号:
    NE/S002510/1
  • 财政年份:
    2019
  • 资助金额:
    $ 6.31万
  • 项目类别:
    Research Grant
NSFGEO-NERC Advancing Predictability of Sea Ice: Phase 2 of the Sea Ice Prediction Network (SIPN2)
NSFGEO-NERC 提高海冰的可预测性:海冰预测网络 (SIPN2) 第二阶段
  • 批准号:
    NE/R017123/1
  • 财政年份:
    2018
  • 资助金额:
    $ 6.31万
  • 项目类别:
    Research Grant
Collaborative Research: Phytoplankton Phenology in the Antarctic: Drivers, Patterns, and Implications for the Adelie Penguin
合作研究:南极浮游植物物候学:对阿德利企鹅的驱动因素、模式和影响
  • 批准号:
    1341547
  • 财政年份:
    2014
  • 资助金额:
    $ 6.31万
  • 项目类别:
    Continuing Grant
Collaborative Research: An innovative network to improve sea ice prediction in a changing Arctic
合作研究:改善北极变化中海冰预测的创新网络
  • 批准号:
    1304246
  • 财政年份:
    2013
  • 资助金额:
    $ 6.31万
  • 项目类别:
    Standard Grant
Collaborative Research: Assessing the Impact of Arctic Sea Ice Variability on the Greenland Ice Sheet Surface Mass and Energy Balance
合作研究:评估北极海冰变化对格陵兰冰盖表面质量和能量平衡的影响
  • 批准号:
    1304807
  • 财政年份:
    2013
  • 资助金额:
    $ 6.31万
  • 项目类别:
    Standard Grant
CDI-Type I: Data Rods: Enabling Time-Series Analysis of Massive Multi-Modality Cryospheric Data
CDI-I 型:数据棒:实现大规模多模态冰冻圈数据的时间序列分析
  • 批准号:
    0941442
  • 财政年份:
    2009
  • 资助金额:
    $ 6.31万
  • 项目类别:
    Standard Grant

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