An optimization experiment was conducted to reproduce the climatological distribution of water properties with an ocean general circulation model in which interior vertical mixing below the surface mixed layer is represented by tidally induced near- and far-field vertical-mixing schemes. Globally constant parameters in the tidally induced mixing schemes along with other physical parameters are optimally estimated based on the Green’s function method. The optimized model performs reasonably well in reproducing the deep-water properties of the Pacific Ocean, suggesting that the combination of tidally induced vertical-mixing schemes is useful in providing a reliable simulation of the deep-ocean state, consistent with both observed broad-scale hydrographic characteristics and recent knowledge of mixing. Adjustment of the parameters in the near-field mixing scheme was effective in improving simulation of the deep-ocean state. These results suggest that the adjustment of a small number of globally constant parameters in tidally induced and other mixing schemes based on recent knowledge of mixing through data assimilation may enable improvements in ocean state estimation throughout the entire water column, including the deep ocean.

进行了优化实验，利用海洋总循环模型重现了水属性的气候分布，在该模型中，潮汐诱导的近场和远场垂直混合方案代表了表面混合层以下的内部垂直混合。潮汐诱导混合方案中的全局常数参数以及其他物理参数是根据格林函数方法最佳估计的。优化的模型在再现太平洋深水特性方面表现相当不错，表明潮汐诱发的垂直混合方案的组合可用于提供可靠的深海状态模拟，这与两个观测到的大尺度一致水文特征和最近的混合知识。调整近场混合方案中的参数对于改善深海状态的模拟是有效的。这些结果表明，基于最近通过数据同化进行混合的知识，对潮汐诱导和其他混合方案中的少量全局常数参数进行调整可以改善整个水柱（包括深海）的海洋状态估计。