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首页> 外文期刊>Physical Oceanography >Assimilation of climatic hydrological data in a Black-Sea model based on the algorithm of adaptive statistics of prognostic errors
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Assimilation of climatic hydrological data in a Black-Sea model based on the algorithm of adaptive statistics of prognostic errors

机译：基于预后误差自适应统计算法的黑海模式气候水文资料同化

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摘要

We propose an algorithm of adaptive statistics of prognostic errors aimed at the assimilation of the climatic temperature and salinity fields in a model of dynamics of the sea. The algorithm is used for the numerical solution of the proposed differential equations for the dispersions of prognostic errors of temperature and salinity. The sources in the equations of advective diffusion of heat and salt depend on the four-dimensional dispersions of prognostic errors and one-dimensional (along the vertical coordinate) dispersions of measurement errors. The dispersions of prognostic errors are corrected at the times of assimilation of the data. We perform the reconstruction and analysis of the climatic fields of currents in the Black Sea. It is shown that the structure of the fields of dispersions in the upper mixed layer is determined by the vertical diffusion. Below this layer, the distribution of dispersions depends on the vertical advection. The algorithm of adaptive statistics of prognostic errors allows us to reconstruct the improved mutually adapted hydrophysical parameters with regard for the dynamics of the dispersions of errors.
机译：我们提出了一种针对海洋动力学模型中气候温度和盐度场同化的预测误差自适应统计算法。该算法用于所提出的温度和盐度预测误差的离散性微分方程的数值解。热量和盐的对流扩散方程式的来源取决于预测误差的四维离散和测量误差的一维（沿垂直坐标）离散。在吸收数据时校正了预后错误的离散度。我们进行了黑海海流气候场的重建和分析。结果表明，上部混合层中的色散场的结构由垂直扩散决定。在该层以下，分散体的分布取决于垂直对流。预测误差的自适应统计算法使我们能够针对误差离散度的动态重建改进的相互适应的水文物理参数。

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