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

北极是地球上最具活力和变化最快的地区之一。过去40年里，海冰在所有季节都持续消失，地表变暖速度比全球平均水平快两到三倍。气候模型与有限的观测数据相结合，已成为研究快速变化的北极气候及其影响的关键工具。然而，正如最近的研究所强调的那样，气候模型模拟中的许多差异和不确定性阻碍了进展。因此，迫切需要集中精力更好地量化、理解和限制北极气候模拟中的模型不确定性，而这种努力必须建立在对控制北极气候变化和变异性的关键物理过程的更好理解的基础上。这项研究将重点关注海洋和大气从中纬度和热带地区向北极的热量输送，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约束，这是更好地了解海洋和大气热传输对北极变暖和海冰融化的影响程度，以及北极变暖对极地热传输和北半球天气和气候的调节程度的必要步骤。该项目将更深入地了解北极气候的关键物理过程和相关模型的不确定性，从而改进对北极和北半球气候的预测和预测，并将惠及广泛的最终用户应用，例如天气预报、渔业管理、土地利用、商业航运、商业保险和海军行动。这项工作包括指导本科生、向公众和 K-12 公立学校推广以及培训博士后科学家。该项目将调查北极气候变率和变化的驱动因素和影响，特别关注：（1）了解海洋和大气向极地热传输的作用； (2) 根据现有观测结果量化影响极地热传输的模型偏差； (3) 评估关键模型偏差对模拟北极气候变率和变化的影响； (4) 限制这些不确定性，以实现对北极气候及其影响的更稳健的预测和预测。为了实现这些目标，该项目将利用各种配置的前所未有的大型社区地球系统模型模拟套件，结合可用的观测和再分析数据集以及提交给耦合模型比对项目第六阶段的模拟。除了分析这些数据集外，还将进行有限的气候模型实验，以量化关键模型偏差对北冰洋（包括海冰）模拟平均状态、变异性和可预测性的影响。该奖项反映了 NSF 的法定使命，并被认为值得支持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。

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.