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Inverse estimation of empirical parameters used in a regional ocean circulation model

机译:区域海洋环流模型中经验参数的反估计

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Significant impacts of the subgridscale parameterizations have been emphasized in modeling the ocean circulations, but various different parameter values are applied to similar numerical studies often without any justification. This study objectively estimates a set of empirical parameters along with their uncertainty for circulation modeling of the East Asian Marginal Seas. The solutions for 14 major parameters are obtained by using model Green’s functions with constraints of climatological temperature and salinity data. The largest cost function reduction occurs in the eastern Japan Sea associated with the sharp gradient of the Polar Front. The calibrated parameters are also validated with realistic transport and path of the Kuroshio in the final experiment. The inverse estimation shows that freshwater discharges from small rivers can be attributed to the coastal precipitation over a strip of land 74–81?km wide. The thickness diffusion coefficient may be similar to the isopycnal and horizontal diffusion coefficients in their magnitude. The accelerated initial condition also contributes to the cost function reduction resulting in weaker trends of deep temperature. Most importantly, estimated scaling factors suggest a significant reduction of the reanalyzed wind stress data for more realistic ocean circulations. Possible reasons for the momentum missing are also discussed.
机译:在模拟海洋环流过程中已强调了亚网格尺度参数化的重大影响,但各种不同的参数值通常在没有任何理由的情况下应用于相似的数值研究。这项研究客观地估计了一组经验参数以及它们对东亚边缘海环流模型的不确定性。通过使用格林模型的功能,并结合气候温度和盐度数据的约束,可以获得14个主要参数的解决方案。最大的成本函数下降发生在日本海东部,与极地锋的陡峭坡度有关。在最终实验中,校准参数也通过黑潮的真实传输和路径进行了验证。反演估计表明,小河流的淡水排放可归因于74-81?km宽的一块土地上的沿海降水。厚度扩散系数的大小可以与等渗和水平扩散系数相似。加速的初始条件还有助于降低成本函数,从而导致较弱的深部温度趋势。最重要的是,估计的比例因子表明,对于更真实的海洋环流,重新分析的风应力数据将大大减少。还讨论了动量缺失的可能原因。

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