Collaborative Research: Towards advanced understanding and improved decadal/centennial prediction of Arctic sea ice state and climate change

合作研究：深入了解和改进北极海冰状态和气候变化的十年/百年预测

• 批准号: 1107788
• 负责人: John Cassano
• 金额: $ 18.22万
• 依托单位: University of Colorado at Boulder
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-10-01 至 2015-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1107788&HistoricalAwards=false
• 关键词: Collaborative; Research; Towards; advanced; understanding

The overarching goal of the project is to advance understanding of Arctic climate system operation and variability to improve model prediction of Arctic climate change at decadal to centennial scales. A set of specific objectives is proposed centered on the following main science hypothesis:Given the projections of continued global warming and its northern high-latitude amplification, the Arctic will become nearly ice-free during summer in the near future, resulting in altered physical state of and interconnections within the Arctic climate system.To confirm or disprove the above hypothesis, our approach is to use subsets of model components and fully coupled RACM to address the following specific objectives:- Identify potential improvements in the simulated sea ice thickness distribution and deformation due to increasing model resolution and representation of fine-scale ice-ocean interactions- Investigate effects of shrinking and thinning sea ice on ice kinematics and its consequences on changing air-ice and ice-ocean interactions- Examine and quantify consequences of melting sea ice on the increased upper ocean heat content and its potential for increased ice melt due to a positive ice-ocean feedback loop- Assess the influence of excess oceanic heat release, especially in fall and winter, on potentially enhancing cyclonic tendency in the atmosphere- Explore the importance of increased sea ice melt and runoff to the Arctic hydrological cycle and its acceleration in the context of first-year ice growth and survival- Integrate positive and negative feedback processes into model simulations of warming climate scenario to determine their net impact on the long-term state of Arctic ice cover- Identify physical and numerical requirements of future GCMs to significantly improve model skill in representing past and present and in predicting future Arctic climate change.A hierarchy of well designed one-way and fully coupled regional climate system model experiments will focus on the above objectives. Such experiments will provide advanced insight into the behavior of the Arctic climate system that is not currently attainable using either individual regional component models or GCMs. The proposed project helps to lay the foundation for a community regional Arctic System Model as recommended in the recently published report to NSF. This research will also address or facilitate other studies related to potential implications of Arctic sea ice melt and warming climate, including consequences for the global ocean thermohaline circulation, Greenland ice sheet, ecosystem, shipping, natural resource development, policymaking and defense. Output from the baseline simulations will be made available to the community through either the ARCSS Data Coordination Center or a Live Access Server at the Naval Postgraduate School, to be developed in support of this project.

该项目的总体目标是增进对北极气候系统运行和变异性的了解，以改进对十年至百年尺度的北极气候变化的模型预测。围绕以下主要科学假设提出了一系列具体目标：鉴于全球持续变暖及其北部高纬度放大的预测，在不久的将来，北极在夏季将几乎无冰，导致北极气候系统的物理状态和内部互连发生改变。为了证实或反驳上述假设，我们的方法是使用模型组件的子集和完全耦合的RACM来解决以下具体问题 目标：- 确定由于模型分辨率和细尺度冰-海相互作用的提高而对模拟海冰厚度分布和变形的潜在改进- 研究海冰收缩和变薄对冰运动学的影响及其对空气-冰和冰-海相互作用变化的影响- 检查并量化海冰融化对上层海洋热含量增加的影响以及由于正冰-海反馈循环而增加冰融化的可能性- 评估 过度海洋热量释放，特别是在秋季和冬季，对潜在增强大气气旋趋势的影响 - 探索海冰融化和径流增加对北极水文循环的重要性及其在第一年冰生长和生存的背景下加速 - 将正反馈过程和负反馈过程纳入气候变暖情景的模型模拟中，以确定其对北极冰盖长期状态的净影响 - 确定未来的物理和数值要求 GCM 将显着提高代表过去和现在以及预测未来北极气候变化的模型技能。精心设计的单向和完全耦合的区域气候系统模型实验的层次结构将集中于上述目标。此类实验将提供对北极气候系统行为的深入了解，而目前使用单独的区域成分模型或全球气候模型无法实现这一点。 拟议的项目有助于为社区区域北极系统模型奠定基础，正如最近向 NSF 发布的报告中所建议的那样。这项研究还将解决或促进与北极海冰融化和气候变暖的潜在影响相关的其他研究，包括对全球海洋温盐环流、格陵兰冰盖、生态系统、航运、自然资源开发、政策制定和国防的影响。基线模拟的输出将通过 ARCSS 数据协调中心或海军研究生院的实时访问服务器提供给社区，以支持该项目。