FAST FOURIER TRANSFORM ENSEMBLE KALMAN FILTER WITH APPLICATION TO A COUPLED ATMOSPHERE-WILDLAND FIRE MODEL
FAST FOURIER TRANSFORM ENSEMBLE KALMAN FILTER WITH APPLICATION TO A COUPLED ATMOSPHERE-WILDLAND FIRE MODEL
复制标题
快速傅里叶变换系综卡尔曼滤波器在大气-荒地火灾耦合模型中的应用
DOI：
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发表时间：
2010
期刊：
影响因子：
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通讯作者：
V. Kondratenko
中科院分区：
文献类型：
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作者：
J. Mandel;J. Beezley;V. Kondratenko
我们提出了一种新型的Ensemble卡尔曼滤波器（EnKF），它使用快速傅立叶变换（FFT）的协方差估计从一个非常小的合奏与自动锥形，并通过卷积的分析合奏的快速计算，避免了需要解决稀疏系统与锥形矩阵。该方法与变形EnKF相结合，使位置误差的校正，除了幅度误差，并证明WRF火，天气研究预报（WRF）模型加上水平集方法实现的再传播模型。
We propose a new type of the Ensemble Kalman Filter (EnKF), which uses the Fast Fourier Transform (FFT) for covariance estimation from a very small ensemble with automatic tapering, and for a fast computation of the analysis ensemble by convolution, avoiding the need to solve a sparse system with the tapered matrix. The method is combined with the morphing EnKF to enable the correction of position errors, in addition to amplitude errors, and demonstrated on WRF-Fire, the Weather Research Forecasting (WRF) model coupled with a re spread model implemented by the level set method.