A new localization implementation scheme for ensemble data assimilation of non-local observations
A new localization implementation scheme for ensemble data assimilation of non-local observations
复制标题
一种新的非本地观测集合数据同化本地化实现方案
DOI：
10.1111/j.1600-0870.2010.00486.x
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发表时间：
2011-01
影响因子：
2
通讯作者：
Zhu, Jiang
中科院分区：
文献类型：
--
作者：
Zheng, Fei;Li, XiChen;Zhu, Jiang
在小尺度集合成员的集合同化中，常采用局部化技术。它有效地消除了背景的虚假相关，提高了系统的秩。然而，在目前的本地化方案的一个缺点是，它是难以实现的同化的非本地观测。在本文中，我们测试了一个新的本地化的实施方案，可以直接同化非本地的意见，而无需精确定位。该方法首先对经典的局部支持相关函数矩阵进行采样，得到一组局部相关函数系综成员（大小为M）.然后，将动力学系综（规模为N）与局域相关函数系综进行组合，利用Schur积将每个动力学系综与每个局域相关函数系综相乘，得到一个N × M系综.证明了由N×M个成员构造的协方差矩阵近似于局部支持相关矩阵与动态协方差矩阵的Schur积。用一个线性平流模式和一个中间耦合模式同化了局地和非局地观测资料，验证了该方案的正确性。分析结果表明，该方案在以较小的动力学系综规模提供合理、高质量的分析场方面是可行和有效的。
Localization technique is commonly used in ensemble data assimilation of small-size ensemble members. It effectively eliminates the spurious correlations of the background and increases the rank of the system. However, one disadvantage in current localization schemes is that it is difficult to implement the assimilation of non-local observations. In this paper, we test a new localized implementation scheme that can directly assimilate non-local observations without pinpointing them. A classical local support correlation functionmatrix is first sampled by a set of local correlation function ensemble members (the size is M). Then, the dynamical ensemble (the size is N) is combined with the local correlation function ensemble to form an N × M ensemble by multiplying each dynamical member with each local correlation function member using the Schur product. The covariance matrix constructed by the N×M members is proved to approximate the Schur product of the local support correlation matrix and the dynamical covariance matrix. This scheme is verified through assimilating both local and non-local observations with a linear advection model and an intermediate coupled model. The analysis results show that this scheme is feasible and effective in providing reasonable and high-quality analysis fields with a relatively small dynamical ensemble size.
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DOI：
10.1111/j.1600-0870.2008.00372.x
发表时间：
2009-01-01
影响因子：
2
作者：
Bishop, Craig H.;Hodyss, Daniel
通讯作者：
Hodyss, Daniel
影响因子：
8.9
作者：
M. Buehner;M. Charron
通讯作者：
M. Buehner;M. Charron
影响因子：
3.2
作者：
Whitaker, Jeffrey S.;Hamill, Thomas M.;Toth, Zoltan
通讯作者：
Toth, Zoltan
DOI：
10.1111/j.1600-0870.2007.00372.x
发表时间：
2009-01
期刊：
Tellus A: Dynamic Meteorology and Oceanography
影响因子：
--
作者：
C. Bishop;D. Hodyss
通讯作者：
C. Bishop;D. Hodyss
影响因子：
3.2
作者：
P. Sakov;P. Oke
通讯作者：
P. Sakov;P. Oke