The Kalmag model as a candidate for IGRF-13
The Kalmag model as a candidate for IGRF-13
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DOI：
10.1186/s40623-020-01295-y
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发表时间：
2020-10-29
影响因子：
3
通讯作者：
Sanchez, Sabrina
中科院分区：
文献类型：
--
作者：
Baerenzung, Julien;Holschneider, Matthias;Sanchez, Sabrina
我们提出了一个新的模型，地磁场跨越过去20年，称为Kalmag。该方法通过对CHAMP和Swarm矢量场观测值的同化，利用参数化的先验协方差矩阵分离对观测场的不同贡献。为了使反问题在数值上是可行的，它已被序列化的时间通过卡尔曼滤波器和平滑算法的组合。该模型提供了可靠的估计过去，现在和未来的平均场和相关的不确定性。这里介绍的版本是我们IGRF候选的更新;同化数据的数量增加了一倍，考虑的时间窗口从[2000.5，2019.74]扩展到[2000.5，2020.33]。
We present a new model of the geomagnetic field spanning the last 20 years and called Kalmag. Deriving from the assimilation of CHAMP and Swarm vector field measurements, it separates the different contributions to the observable field through parameterized prior covariance matrices. To make the inverse problem numerically feasible, it has been sequentialized in time through the combination of a Kalman filter and a smoothing algorithm. The model provides reliable estimates of past, present and future mean fields and associated uncertainties. The version presented here is an update of our IGRF candidates; the amount of assimilated data has been doubled and the considered time window has been extended from [2000.5, 2019.74] to [2000.5, 2020.33].