Collaborative research: Ocean mixing processes associated with high spatial heterogeneity in sea ice and the implications for climate models

合作研究：与海冰高度空间异质性相关的海洋混合过程及其对气候模型的影响

• 批准号: 0968676
• 负责人: Meibing Jin
• 金额: $ 67.68万
• 依托单位: University of Alaska Fairbanks Campus
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-06-01 至 2015-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0968676&HistoricalAwards=false
• 关键词: Collaborative; research; Ocean; mixing; processes

Previous work, using of a single column ice-ocean model, showed that resolving the high spatial variability in ice-ocean brine exchange has important implications for ocean mixing and consequent sea ice mass budgets that influence critical climate feedbacks. In particular, multiple ocean columns in each grid with leads that are realistically embedded within the ice cover were needed to improve simulations against Surface Heat Budget for the Arctic Ocean (SHEBA) observations. Currently, this method has not been tested or implemented in any climate models. Since the single column ice-ocean model study was limited to the summer ice melting season and in a 1-D format only, funds are provided to allow further studies on the multi-column ocean grid (MCOG) and related processes. Questions to be explored include: How does MCOG work during the ice growth period? How can MCOG be implemented in 3-D climate models? How does MCOG influence physical and biogeochemical tracers that have fluxes between ice and ocean? How much can MCOG reduce uncertainties in climate models? What is the importance of explicitly representing the high ice/ocean flux spatial heterogeneity in climate processes and feedbacks? How will representing this sub-gridscale variability reduce uncertainties in climate models? A more systematic study and implementation of MCOG in climate models to reduce uncertainties associated with the high spatial heterogeneity in sea ice is the focus of this study. A Climate Process and Modeling Team will address MCOG-related problems and implementation in climate models systematically. The following studies are planned:1) Use sea ice and ocean field data and a small regional ice-ocean model with and without MCOG to quantify key parameters and investigate climate and biogeochemical processes influenced by the MCOG, 2) Implement the MCOG scheme in the Community Climate System Model (CCSM) and GFDL climate models, conduct long-term runs, and investigate the influence on climate and biogeochemical feedbacks,3) Validate the new model with observations, and conduct model inter-comparison with other Intergovernmental Panel on Climate Change (IPCC) climate models, and4) Solicit more climate model users to participate in using and assessing the new method through workshops, web-based communications, and distribution of the new model code.

以前的工作，使用单柱冰-海洋模型，表明解决冰-海洋盐水交换的高空间变异性对海洋混合和随后的海冰质量预算具有重要意义，这些预算影响关键的气候反馈。特别是，需要在每个网格中使用实际嵌入冰盖内的引线的多个海洋柱，以改善对北冰洋表面热收支（SHEBA）观测的模拟。目前，这种方法尚未在任何气候模型中进行测试或实施。由于单柱冰-海洋模式研究仅限于夏季冰融化季节，并且仅采用一维格式，因此提供资金以允许对多柱海洋网格（MCOG）和相关过程进行进一步研究。需要探讨的问题包括：MCOG在冰生长期间是如何工作的？如何在3-D气候模式中实现MCOG？MCOG如何影响在冰和海洋之间有通量的物理和地球化学示踪剂？MCOG能在多大程度上减少气候模型的不确定性？在气候过程和反馈中明确表现高冰/海洋通量空间异质性的重要性是什么？如何代表这种次网格尺度的变化减少气候模型的不确定性？更系统的研究和实施MCOG气候模式，以减少与海冰的高度空间异质性的不确定性是这项研究的重点。一个气候过程和建模小组将系统地解决与MCOG有关的问题和气候模型的实施。计划开展以下研究：1）使用海冰和海洋场数据以及一个小型区域冰-海模式（有和没有MCOG）来量化关键参数并研究MCOG影响的气候和地球化学过程; 2）在社区气候系统模式（CCSM）和GFDL气候模式中实施MCOG方案，进行长期运行，并研究对气候和地球化学反馈的影响; 3）将新模式与观测结果进行对比，并与其他政府间气候变化专门委员会（IPCC）气候模式进行比较; 4）通过研讨会，基于网络的交流，并分发新型号代码。