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。在过去的40年里，所有季节的海冰都在持续减少，地表变暖的速度比全球平均速度快两到三倍。气候模型与有限的观测数据相结合，是研究北极气候快速变化及其影响的关键工具。然而，正如最近的研究所强调的那样，气候模式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、理解和约束北极气候模拟模式的不确定性，而这种努力必须基于对控制北极气候变化和变率的关键物理过程的更好理解。本研究将重点研究中纬度和热带地区海洋和大气向北极的热量输送，这是影响北极气候的关键过程之一。该项目将改善模式不确定性的约束，这是更好地了解海洋和大气热输送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输送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式的不确定性，从而改进对北极和北半球气候的预测和预估，并将有利于广泛的最终用户应用，如天气预报、渔业管理、土地利用、商业航运、商业保险和海军作战。这项工作包括指导本科生，向公众和K-12公立学校推广，以及培养一名博士后科学家。该项目将研究北极气候变率和变化的驱动因素和影响，重点关注：(1)了解海洋和大气对极地热输送的作用；(2)根据现有观测资料量化影响向极地热输运的模式偏差；(3)评估关键模式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可靠的预测和预估。为了实现这些目标，该项目将利用空前庞大的各种配置的社区地球系统模型模拟，结合现有的观测和再分析数据集，以及提交给耦合模型比对项目第6阶段的模拟。除了分析这些数据集之外，还将进行有限的气候模式实验，以量化关键模式偏差对北冰洋（包括海冰）模拟平均状态、变率和可预测性的影响。该奖项反映了美国国家科学基金会的法定使命，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。

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.