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A suboptimal data assimilation algorithm based on the ensemble Kalman filter

机译:基于集合卡尔曼滤波的次优数据同化算法

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摘要

A suboptimal algorithm for data assimilation based on the ensemble Kalman filter (EnKF) is proposed. An advantage of the algorithm is that it does not require an additional calculation of the ensemble of perturbations that correspond to the analysis-error covariance matrix because it is calculated automatically with this algorithm. The operation count of the algorithm is close to that of the local ensemble transform Kalman filter (LETKF), but its formulae are different from those of the LETKF.
机译:提出了一种基于集合卡尔曼滤波器(EnKF)的次优数据同化算法。该算法的一个优点是它不需要对与分析误差协方差矩阵相对应的扰动集合进行额外的计算,因为它是使用此算法自动计算的。该算法的运算次数与局部集合变换卡尔曼滤波器(LETKF)的运算次数相近,但其公式与LETKF的公式不同。

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