Collaborative Research: Ocean Mixing Processes Associated with High Spatial Heterogeneity in Sea Ice and the Implications for Climate Models

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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.