Collaborative Research: Thermodynamic and Dynamic Drivers of the Arctic Sea Ice Mass Budget at MOSAiC

合作研究：MOSAiC 北极海冰质量预算的热力学和动态驱动因素

• 批准号: 1722729
• 负责人: Jennifer Hutchings
• 金额: $ 35.39万
• 依托单位: Oregon State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-10-01 至 2022-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1722729&HistoricalAwards=false
• 关键词: Collaborative; Research; Thermodynamic; Dynamic; Drivers

Energy fluxes to the sea ice, and the processes that control them in time and space, comprise some of the largest uncertainties in current models of the central Arctic system and are likely changing as the sea ice thins. This project will make observations to provide the type of information that model developers need for representing emergent Arctic processes. These observations will be the first set of comprehensive, coupled atmosphere-ice-ocean energy and momentum flux measurements collected within a well-defined network. They will enable a process-based understanding of ice thermodynamics and dynamics via synergistic use of a coupled model. The Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition is a tremendous opportunity to leverage large US and international investments MOSAiC is motivated by the changing Arctic system and declining sea ice, and their significant implications for the global climate system and numerous stakeholders. The initiative seeks to address leading deficiencies in model representation of coupled, atmosphere-ice-ocean processes in the Arctic system through intensive, year-round observations from a drifting station in the central Arctic and coordinated multi-scale modeling. This project will examine the detailed interplay of sea-ice thermodynamic and dynamic processes and how they control the state of the ice over a full year. This project will entail an observational array of five nodes installed at approximately 15 km separation in the central Arctic sea ice, each of which has systems to measure continuously the states of the upper ocean and lower atmosphere, the heat and momentum fluxes from the ocean and atmosphere to the ice, and the ice thermodynamic state and mass balance. A network of position buoys will be used to measure ice movement and deformation across the observing domain. Regional, coupled-system model simulations will provide the means to synthesize observational information towards process understanding. Together these tools will be used to build comprehensive sea ice energy, upper ocean heat, and sea-ice momentum budgets, examine how these co-vary in space and time over all seasons, and develop temporally-evolving process relationships among multiple key parameters. They will use the detailed observations and coupled regional model to examine how energy transfer processes (thermodynamics) are influenced by sea-ice deformation (dynamics) on sub-seasonal to seasonal time scales, and they will assess sea-ice predictability related to dynamic and thermodynamic process relationships, using a full year of quasi-operational, 10-day sea-ice forecasts. Improved predictive models are an important means for addressing major societal needs related to Arctic change and declining sea ice. The project will provide an observational and process-based foundation for model development that has been called for by model developers and international experts. Moreover, it will offer insight into the sources of sea ice predictability, which will help to constrain future research pathways for improved sea ice models. The observations will enable a wide array of coupled system research that reaches well beyond the proposed project to impact research on other aspects of the Arctic physical, biological, and biogeochemical systems. Moreover, this project will support development towards autonomous ocean and atmospheric flux measurements that will help fill critical gaps in the Arctic observing network. Educational content developed around the project's research themes will support student learning on the physics of the Arctic system and enable broader scientific outreach efforts.

流向海冰的能量通量，以及在时间和空间上控制它们的过程，构成了北极中部系统当前模型中一些最大的不确定性，而且可能会随着海冰变薄而发生变化。该项目将进行观测，以提供模型开发人员表示北极新兴过程所需的信息类型。这些观测将是在一个定义明确的网络内收集的第一组全面的、耦合的大气-冰-海洋能量和动量通量测量。它们将通过耦合模型的协同使用，实现对冰热力学和动力学的基于过程的理解。研究北极气候的多学科漂流观测站(MOSAIC)考察是利用美国和国际上的大量投资的一个巨大机会。MOSAIC的动机是不断变化的北极系统和不断减少的海冰，以及它们对全球气候系统和众多利益攸关方的重大影响。该倡议寻求通过北极中部一个漂流站的全年密集观测和协调的多尺度模拟，解决北极系统中耦合的大气-冰-海洋过程的模式表示方面的主要缺陷。该项目将详细研究海冰热力学和动力过程的相互作用，以及它们如何控制全年的冰状态。该项目将需要在北极中部海冰上安装一个间隔约15公里的五个节点的观测阵列，每个节点都有连续测量上层海洋和低层大气状态、从海洋和大气到冰的热量和动量通量以及冰的热力学状态和质量平衡的系统。将使用位置浮标网络来测量观测区域内的冰移动和变形。区域耦合系统模型模拟将提供综合观测信息以了解过程的手段。这些工具将一起用于建立全面的海冰能量、上层海洋热量和海冰动量预算，研究这些在所有季节的空间和时间上是如何共同变化的，并在多个关键参数之间建立时间演变的过程关系。他们将利用详细的观测和耦合的区域模式，在分季节到季节性的时间尺度上审查海冰变形(动力学)如何影响能量转移过程(热力学)，并将利用一整年的准业务10天海冰预报，评估与动力和热力学过程关系有关的海冰可预报性。改进的预测模型是解决与北极变化和海冰减少有关的主要社会需求的重要手段。该项目将为模型开发人员和国际专家所呼吁的模型开发提供一个观察性和基于过程的基础。此外，它将提供对海冰可预测性来源的洞察，这将有助于限制未来改进海冰模型的研究途径。这些观察将使广泛的耦合系统研究能够远远超出拟议的项目，影响对北极物理、生物和生物地球化学系统其他方面的研究。此外，该项目将支持自主海洋和大气通量测量的发展，这将有助于填补北极观测网络的关键空白。围绕该项目的研究主题开发的教育内容将支持学生学习北极系统的物理，并使更广泛的科学推广工作成为可能。

项目成果

Thermodynamic and dynamic contributions to seasonal Arctic sea ice thickness distributions from airborne observations

机载观测对北极季节性海冰厚度分布的热力学和动力学贡献

• DOI: 10.1525/elementa.2021.00074
• 发表时间: 2022
• 期刊: Elementa: Science of the Anthropocene
• 作者: von Albedyll, Luisa;Hendricks, Stefan;Grodofzig, Raphael;Krumpen, Thomas;Arndt, Stefanie;Belter, H. Jakob;Birnbaum, Gerit;Cheng, Bin;Hoppmann, Mario;Hutchings, Jennifer
• 通讯作者: Hutchings, Jennifer

Comparisons of sea ice motion and deformation, and their responses to ice conditions and cyclonic activity in the western Arctic Ocean between two summers

• DOI: 10.1016/j.coldregions.2019.102925
• 发表时间: 2020-02
• 期刊: Cold Regions Science and Technology
• 影响因子: 4.1
• 作者: R. Lei;Dawei Gui;P. Heil;J. Hutchings;M. Ding

Annual Cycles of Sea Ice Motion and Deformation Derived From Buoy Measurements in the Western Arctic Ocean Over Two Ice Seasons

• DOI: 10.1029/2019jc015310
• 发表时间: 2020-06
• 期刊: Journal of Geophysical Research: Oceans
• 作者: R. Lei;Dawei Gui;J. Hutchings;P. Heil;Na Li

Estimating statistical errors in retrievals of ice velocity and deformation parameters from satellite images and buoy arrays

估计从卫星图像和浮标阵列反演冰速度和变形参数的统计误差

• DOI: 10.5194/tc-14-2999-2020
• 发表时间: 2020
• 期刊: The Cryosphere
• 作者: Dierking, Wolfgang;Stern, Harry L.;Hutchings, Jennifer K.
• 通讯作者: Hutchings, Jennifer K.

Seasonality and timing of sea ice mass balance and heat fluxes in the Arctic transpolar drift during 2019–2020

• DOI: 10.1525/elementa.2021.000089
• 发表时间: 2022
• 期刊: Elementa: Science of the Anthropocene
• 作者: R. Lei;B. Cheng;M. Hoppmann;Fanyi Zhang;Guangyu Zuo;J. Hutchings;Long Lin;Musheng Lan;Hangzhou Wang;J. Regnery;T. Krumpen;J. Haapala;B. Rabe;D. Perovich;M. Nicolaus