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

先前使用单柱冰-海模式的工作表明，解决冰-海盐水交换的高空间变异性对影响关键气候反馈的海洋混合和随之而来的海冰质量预算具有重要意义。特别是，需要在每个网格中设置多个海洋柱，其引线实际嵌入冰盖中，以改进针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。由于单柱海冰-海洋模式研究仅限于夏季海冰融化季节，并且仅采用一维格式，因此提供了资金以允许进一步研究多柱海洋网格（MCOG）及其相关过程。要探讨的问题包括：MCOG在冰的生长期间是如何工作的？如何在三维气候模型中实现MCOG ？MCOG如何影响在冰和海洋之间具有通量的物理和生物地球化学示踪剂？MCOG能在多大程度上减少气候模式的不确定性？在气候过程和反馈中明确表示高冰/海洋通量空间异质性的重要性是什么？如何表示这种亚网格尺度的变率来减少气候模式中的不确定性？本研究的重点是在气候模式中更系统地研究和实施MCOG，以减少与海冰高度空间异质性相关的不确定性。气候过程和模拟小组将系统地处理与mcog相关的问题和气候模式的实施。计划开展以下研究：1)利用海冰和海洋实测数据以及有和没有MCOG的小型区域冰-海洋模式，量化关键参数，研究MCOG对气候和生物地球化学过程的影响；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，研究对气候和生物地球化学反馈的影响；3)用观测资料验证新模式。并与其他政府间气候变化专门委员会（IPCC）气候模式进行相互比较。4)通过研讨会、网络交流和新模式代码的分发，邀请更多的气候模式用户参与新方法的使用和评估。

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.