Collaborative Research: Constraining Uncertainty in Arctic Climate Variability, Change, and Impacts Through Process-Based Understanding

合作研究：通过基于过程的理解来限制北极气候变率、变化和影响的不确定性

• 批准号: 2106228
• 负责人: Gokhan Danabasoglu
• 金额: $ 44.69万
• 依托单位: University Corporation For Atmospheric Res
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-01 至 2024-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2106228&HistoricalAwards=false
• 关键词: Collaborative; Research; Constraining; Uncertainty; Arctic

The Arctic is one of the most dynamic and fastest changing regions on the Earth. It has exhibited continued loss of sea-ice in all seasons over the past 40 years as well as surface warming at a pace two to three times faster than the global average. Climate modeling, combined with limited observational data, has been a key tool to investigate the rapidly changing Arctic climate and the implications of that change. Progress, however, has been hampered by many differences and uncertainties in climate model simulations, as highlighted in recent studies. Therefore, a focused effort to better quantify, understand, and constrain model uncertainties in simulations of Arctic climate is urgently needed and such an effort must be based on improved understanding of the key physical processes governing Arctic climate change and variability. This research will focus on the transport of heat by ocean and atmosphere from the mid-latitudes and tropics to the Arctic, one of the key processes impacting Arctic climate. The project will improve constraints of model uncertainties, a necessary step toward better understanding to what degree the ocean and atmosphere heat transports contribute to the Arctic warming and sea-ice melting, as well as how much the Arctic warming modulates the poleward heat transport and Northern Hemisphere weather and climate. The project will provide a deeper understanding of the key physical processes for the Arctic climate and associated model uncertainties, which can lead to improved predictions and projections for the Arctic and Northern Hemisphere climate and would benefit a wide range of end-user applications, such as weather forecasting, fisheries management, land use, commercial shipping, commercial insurance, and naval operations. The effort includes mentoring of undergraduate students, outreach to the general public and K-12 public schools, and training of a postdoctoral scientist. This project will investigate the drivers and impacts of Arctic climate variability and change, specifically focusing on: (1) understanding the role of poleward heat transport by the ocean and atmosphere; (2) quantifying the model biases influencing the poleward heat transport against available observations; (3) assessing the impact of key model biases in simulated Arctic climate variability and change; and (4) constraining these uncertainties to achieve more robust predictions and projections of the Arctic climate and its impacts. To address these goals, the project will utilize an unprecedentedly large suite of Community Earth System Model simulations in various configurations in conjunction with available observational and reanalysis data sets as well as simulations submitted to the Coupled Model Intercomparison Project phase 6. In addition to analyzing these data sets, limited climate model experiments will be conducted to quantify the impacts of a key model bias on the simulated mean state, variability, and predictability in the Arctic Ocean, including sea ice.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.

北极是地球上最动态和最快的地区之一。在过去的40年中，它在所有季节中都表现出持续的海冰，并且以比全球平均水平快两到三倍的速度变暖。气候建模与有限的观察数据相结合，一直是研究快速变化的北极气候及其含义的关键工具。然而，正如最近的研究中强调的那样，在气候模型模拟中，许多差异和不确定性都阻碍了进步。因此，迫切需要在北极气候模拟中更好地量化，理解和限制模型不确定性的集中精力，并且必须基于对北极气候变化和可变性的关键物理过程的提高理解。这项研究将集中于海洋和大气从中期和热带地区到北极的运输，这是影响北极气候的关键过程之一。该项目将改善模型不确定性的限制，这是更好地理解海洋和大气热传输的必要步骤，这有助于北极变暖和海冰融化，以及北极变暖的程度调节了极端的热量运输以及北半球的天气和气候。该项目将对北极气候和相关模型不确定性的关键物理过程有更深入的了解，这可以改善对北极和北半球气候的预测和预测，并将受益于广泛的最终用户应用，例如风化，渔业管理，渔业管理，土地使用，商业运输，商业运输，商业保险，商业​​保险和海军运营。这项工作包括指导本科生，向公众和K-12公立学校的宣传以及对博士后科学家的培训。该项目将调查北极气候变化和变化的驱动因素和影响，特别是：（1）了解海洋和大气中极热传输的作用； （2）量化影响极热传输的模型偏向可用观测值； （3）评估关键模型偏见在模拟北极气候变化和变化中的影响； （4）限制这些不确定性以实现北极气候及其影响的更强大的预测和预测。为了解决这些目标，该项目将利用各种配置中的大型社区地球系统模型模拟与可用的可用观察性和重新分析数据集以及向耦合模型对比的耦合模型之间的第6阶段提交的模型，除了分析这些模型的模型和模型的模型外，还将量化的模型，除了分析这些模型的模型外，还可以量化的模型，量化量的模型，将量化的模型量化，除了量化的模型外，量化的模型还可以实现量的模型。北极海洋中的可预测性，包括海冰。该奖项反映了NSF的法定任务，并通过使用基金会的知识分子优点和更广泛的影响审查标准来评估值得支持。