Improve ocean mixing caused by subgrid-scale brine rejection using multi-column ocean grid in a climate model

Heterogeneous ice pack with sporadic narrow but long leads in the polar oceans was unresolved in typical climate model grid. Although multi-category sea ice thickness distribution was used in one sea ice model grid to calculate separate heat, salt and tracer fluxes through each category, the ocean m...

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Bibliographic Details
Main Authors: Jin, Meibing, Hutchings, Jennifer, Kawaguchi, Yusuke, Kikuchi, Takashi
Format: Still Image
Language:English
Published: 2012
Subjects:
Online Access:http://hdl.handle.net/11122/11013
Description
Summary:Heterogeneous ice pack with sporadic narrow but long leads in the polar oceans was unresolved in typical climate model grid. Although multi-category sea ice thickness distribution was used in one sea ice model grid to calculate separate heat, salt and tracer fluxes through each category, the ocean models use only single-column grid to communicate with the averaged fluxes from all categories. When the lead is resolved by the grid, the added salt at the sea surface will sink to the base of the mixed layer and then spread horizontally. When averaged at a climate-model grid size, this vertical distribution of added salt is lead-fraction dependent. When the lead is unresolved, the model errors were systematic leading to greater surface salinity and deeper mixed-layer depth (MLD). An empirical function was developed to revise the added-salt-related parameter n from being fixed to lead-fraction dependent. Application of this new scheme in climate model showed significant improvement in modeled wintertime salinity and MLD as compared to series of CTD data sets in 1997/1998 and 2006/2007. The results showed the most evident improvement in modeled MLD in the Arctic Basin, similar to that using a fixed n = 5, as recommended by the previous Arctic regional model study, in which the parameter n obtained is close to 5 due to the small lead fraction in the Arctic Basin in winter. This work was funded by NSF ARC-0652838, also supported by International Arctic Research Center through JAMSTEC-IARC Research Agreement.