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中国物理学会期刊

一种基于复数域微分的资料同化新方法

CSTR: 32037.14.aps.62.170504

A new data assimilation method using complex-variable differentiation

CSTR: 32037.14.aps.62.170504
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  • 提出了一种基于复数域微分的资料同化新方法. 针对变分资料同化中目标泛函梯度计算复杂和精度不高的问题, 首先利用复变量求导法把梯度分析过程转化为复变泛函的数值计算, 进而高效和高精度地获得梯度值; 然后结合经典的最优化方法, 给出了非线性物理系统资料同化问题的新求解算法; 最后对典型混沌系统和包含开关现象的单格点比湿发展方程进行了资料同化数值实验, 结果表明新方法能非常有效地估计出非线性动力预报模式的初始条件.

     

    A new method for data assimilation is proposed using complex-variable differentiation (CVD), which can be used to estimate the initial conditions of the nonlinear physical system governed by the following equation:. Firstly, the gradient analysis of cost function in variational data assimilation is transformed into function numerical computation in complex domain, and the value of gradient is computed more efficiently and exactly. Secondly, the new algorithm of data assimilation is developed by combining an accurate gradient information from CVD with the classical optimization method. Finally, numerical simulations of typical chaotic systems and a humidity evolution equation with physical on-off process show that the new data assimilation method can reconstruct initial conditions of the nonlinear dynamical system very conveniently and accurately.

     

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