Geomagnetic jerk extraction based on the covariance matrix
Geomagnetic jerk extraction based on the covariance matrix
复制标题
基于协方差矩阵的地磁加加速度提取
DOI：
10.1007/s11770-019-0761-6
复制
发表时间：
2019
影响因子：
0.7
通讯作者：
Shuang Liu
中科院分区：
文献类型：
--
作者：
Yan Feng;Y. Jiang;Jianhua Gu;Fan Xu;Yi Jiang;Shuang Liu
我们对 43 个中国天文台的数据进行归一化，并选择具有最连续记录的 10 个中国天文台的数据，通过计算年度观测值与 CHAOS-6 模型月平均值之间的偏差来评估长期变化 (SV) 和地磁急动。利用残差的协方差矩阵研究了北向、东向和垂直方向特征方向的变化，发现垂直方向受磁层环流的影响很大。为了获得无噪声数据，我们依靠残差的协方差矩阵来消除环电流导致的最大特征值或向量的噪声贡献。最后，我们比较了中国十个天文台和欧洲七个天文台的数据。显然，协方差矩阵方法可以模拟Dst的SV，2014年中国北向分量的加加速度和2003.5年东向分量的加加速度与欧洲垂直向下分量的加加速度高度一致，与CHAOS-6相比，协方差矩阵方法可以显示更多的SV细节。
We normalize data from 43 Chinese observatories and select data from ten Chinese observatories with most continuous records to assess the secular variations (SVs) and geomagnetic jerks by calculating the deviations between annual observed and CHAOS-6 model monthly means. The variations in the north, east, and vertical eigendirections are studied by using the covariance matrix of the residuals, and we find that the vertical direction is strongly affected by magnetospheric ring currents. To obtain noise-free data, we rely on the covariance matrix of the residuals to remove the noise contributions from the largest eigenvalue or vectors owing to ring currents. Finally, we compare the data from the ten Chinese observatories to seven European observatories. Clearly, the covariance matrix method can simulate the SVs of Dst, the jerk of the northward component in 2014 and that of the eastward component in 2003.5 in China are highly agree with that of Vertically downward component in Europe, compare to CHAOS-6, covariance matrix method can show more details of SVs.
地磁场建模中的噪声信号：用于长期变化研究的去噪数据
影响因子：
2.8
作者：
Wardinski
通讯作者：
Wardinski
2003.5-用区域观测站长期变化数据表征的地磁急动
影响因子：
2.3
作者：
Feng Y
通讯作者：
Feng Y