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Linear Versus Nonlinear Methods for Detecting Magnetospheric and Ionospheric Current Systems Patterns

机译:用于检测磁体和电离层电流系统图案的线性与非线性方法

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There is a growing interest in the development of models and methods of analysis aimed to recognize in the geomagnetic field signals the different contributions coming from the various sources both internal and external to the Earth. Many models describing the geomagnetic field of internal and external origin have been developed. Here, we investigate the possibility to recognize in the magnetic field of external origin the different contributions coming from external sources. We consider the measurements of the vertical component of the geomagnetic field recorded by the European Space Agency (ESA) Swarm A and B satellites at low and mid latitudes during a geomagnetically quiet period. We apply two different methods of analysis: a linear method, that is, the empirical orthogonal function (EOF), and a nonlinear one, that is, the multivariate empirical mode decomposition (MEMD). Due to the high nonlinear behavior of the different external contributions to the magnetic signal the MEMD seems to recognize better than EOF the main intrinsic modes capable of describing the different magnetic spatial structures embedded in the analyzed signal. By applying the MEMD only five modes and a residue are necessary to recognize the different contributions coming from the external sources in the magnetic signal against the 26 modes that are necessary in the case of the EOF. This study is an example of the potential of the MEMD to give new insights into the analysis of the geomagnetic field of external origin and to separate the ionospheric signal from the magnetospheric one in a simple and rapid way.
机译:在模型的发展和分析方法的发展中,旨在识别在地磁场中的模型和分析方法的兴趣越来越令人兴趣,信号来自地球内部和外部的各种来源的不同贡献。已经开发出许多模型,描述了内部和外部原点的地磁场。在这里,我们调查了在外部磁场中识别的可能性来自外部来源的不同贡献。我们考虑欧洲航天局(ESA)记录的地磁场的垂直成分的测量在地磁安静时期的低和中纬度地区群体A和B卫星。我们应用两种不同的分析方法:线性方法,即经验正交函数(EOF)和非线性函数,即多元经验模式分解(MEMD)。由于对磁性信号的不同外部贡献的高非线性行为,MEMD似乎识别比EF能够描述在分析信号中嵌入的不同磁空间结构的主要内部模式。通过应用MEMD仅五种模式和残留物是必须识别来自磁信号中的外部源的不同贡献,而在EOF的情况下是必需的26个模式。本研究是MEMD潜力的一个例子,以便在外部原点的地磁场分析中,以简单快速地将电离层信号与磁体信号分开的新洞察。

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