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A regulated localization scheme for ensemble-based Kalman filters

机译:基于集成的卡尔曼滤波器的规范化定位方案

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摘要

Localization is an essential element of ensemble-based Kalman filters in large-scale systems. Two localization methods are commonly used: covariance localization and domain localization. The former applies a localizing weight to the forecast covariance matrix, while the latter splits the assimilation into local regions in which independent assimilation updates are performed. The domain localization is usually combined with observation localization, which is a weighting of the observation-error covariance matrix, resulting in a similar localization effect to that of covariance localized filters. It is shown that the use of the same localization function in covariance localization and observation localization results in distinct effective localization length-scales in the Kalman gain. In order to improve the performance of observation localization, a regulated localization scheme is introduced. Twin experiments with the Lorenz-96 model demonstrate that the regulated localization can lead to a significant reduction of estimation errors as well as increased stability of the assimilation process. Copyright (c) 2011 Royal Meteorological Society
机译:本地化是大规模系统中基于集成的卡尔曼滤波器的基本要素。通常使用两种定位方法:协方差定位和域定位。前者将局部权重应用于预测协方差矩阵,而后者将同化划分为局部区域,在该区域中执行独立的同化更新。通常将域定位与观察定位相结合,观察定位是观察误差协方差矩阵的加权,从而导致与协方差局部滤波器相似的定位效果。结果表明,在协方差定位和观测定位中使用相同的定位函数会导致Kalman增益中不同的有效定位长度尺度。为了提高观测定位的性能,提出了一种规范的定位方案。用Lorenz-96模型进行的两次实验表明,受控的局域化可以显着减少估计误差,并提高同化过程的稳定性。版权所有(c)2011皇家气象学会

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