Collaborative Research: Arctic sea ice variability: Remote drivers and local processes

北极海冰消失是全球社会关注的一个重要问题，影响着北极和全球环境。目前，全球气候模型在预测最近观察到的北极海冰减少方面表现不佳，而且造成这种差异的原因尚不清楚。一种解释是模型可能不够灵敏，无法捕捉海冰对温室变暖的反应。然而，另一种可能性是自然循环加速了近期北极海冰的消失。解决这个问题不仅对解释最近的北极气候变化具有重要意义，而且对北极的未来预测也具有重要意义，包括我们何时会看到北极第一个无冰夏季的问题。该研究将进行有针对性的模拟，并将这些模拟置于过去 117 年的观察背景中。因此，我们希望更好地了解模型如何更好地捕捉北极气候和海冰自然发生的变化，以及如何改进模型以产生更可靠的预测。此外，该研究还将在气候科学和一般气候建模的极地方面培训一名研究生和一名博士后科学家，并将针对圣巴巴拉的 K-12 学生和教师提供外展活动。该项目将帮助我们了解和量化北极的大气环流如何影响风、云量、水蒸气、辐射，从而影响海冰的变化。它将有助于更好地了解强迫变量和内部变量在近期北极变暖和海冰消失中的相对贡献。首先，研究人员将在全球地球系统模型中使用数据同化技术，并通过与高纬度地区的遥相关探索热带海面温度如何导致最近的海冰减少。然后，研究人员将研究将北极环流与热带地区的远程驱动因素联系起来的动力机制，并将过去 40 年的环流变化纳入更长期的百年变化背景中。最后，结果将有助于评估耦合模型比对项目第 5 阶段 (CMIP5) 的模型技能，并确定热带驱动因素是否代表模拟内部变异的主要来源。该奖项反映了 NSF 的法定使命，并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，被认为值得支持。

Arctic sea ice loss is an important concern for global society affecting both Arctic and global environments. At present, global climate models do a poor job of predicting recent observed declines in Arctic sea ice, and the causes of this discrepancy remain unclear. One interpretation is that models may not be sensitive enough to capture the response of sea ice to greenhouse warming. However, another possibility is that natural cycles have accelerated the recent Arctic sea ice loss. Solving this problem has important implications not only for the interpretation of recent Arctic climate change but also the future projection for the Arctic, including the question as to when we will see the first ice free summer in the Arctic. The study will conduct targeted simulations and place these simulations in the context of observations over the last 117 years. As a result, we expect to better understand how well models capture naturally occurring variations of the Arctic climate and sea ice, and how we can improve models to yield more confident predictions. In addition, the study will train a graduate student and a postdoctoral scientist in polar aspects of climate science and general climate modeling and will provide outreach activities targeting K-12 students and teachers in Santa Barbara. This project will help us understand and quantify how atmospheric circulation in the Arctic influences winds, cloudiness, water vapor, radiation and thereby sea ice variability. It will lead to better understanding of the relative contribution of forced and internal variaiblities in recent Arctic warming and sea ice loss. First, the investigators will use data assimilation techniques in a global earth system model and explore how tropical sea surface temperature contributes to the recent sea ice decline via teleconnections to the high latitudes. The investigators will then examine dynamical mechanisms that link Arctic circulation to remote drivers in the tropics and put circulation changes over the last 40 years into the context of longer centennial term changes. Finally, results will help evaluate model skill for Coupled Model Intercomparison Project Phase 5 (CMIP5) and determine whether the tropical drivers represent a main source of modeled internal variability.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.