Magnetic field gradient tensor time series

CDF dataset contains 4-monthly time series of the magnetic field gradient tensor elements, the secular variation field gradient tensor elements, and their associated error estimates, all provided in a global grid of 300 Geomagnetic Virtual Observatories. <br><br>GVOs from Swarm satellite data:SW_OPER_GVOBS_4M_2_20140301T000000_20200301T000000_0201.cdf<br><br>GVOs from CHAMP satellite data:CH_OPER_GVOBS_4M_2_20010301T000000_20100701T000000_0201.cdf<br>The ReadMe.txt file provides details on the datasets and how these are made, version, changelog. In addition, the script GVOgradient_ex.ipynb provides a simple example of how to load and plot the CDF files in Python.<br>The algorithms used to derive the GVO gradient data products are explained in detail in the reference below.<br>Reference:Hammer, M. D, Finlay, C. C, and Olsen, N. (2021) 'Secular Variation Signals in Magnetic Field Gradient Tensor Elements derived from satellite-based Geomagnetic Virtual Observatories', submitted to GJI<br><br>

CDF数据集包含每4个月一次的时间序列数据，涵盖磁场梯度张量元素、长期变化磁场梯度张量元素及其相关误差估计，所有数据均在由300个地磁虚拟观测站（Geomagnetic Virtual Observatory，简称GVO）组成的全球网格中提供。<br><br>来自Swarm卫星数据的GVO：SW_OPER_GVOBS_4M_2_20140301T000000_20200301T000000_0201.cdf<br><br>来自CHAMP卫星数据的GVO：CH_OPER_GVOBS_4M_2_20010301T000000_20100701T000000_0201.cdf<br>ReadMe.txt文件提供了数据集的详细信息、生成方法、版本及更新日志。此外，脚本GVOgradient_ex.ipynb提供了在Python中加载和绘制CDF文件的简单示例。<br>推导GVO梯度数据产品所使用的算法详见下述参考文献。参考文献：Hammer, M. D, Finlay, C. C, and Olsen, N. (2021)《基于卫星地磁虚拟观测站的磁场梯度张量元素长期变化信号》，已提交至GJI。