Empirical Modeling of Planetary Magnetospheres in Response to Solar Wind Dynamics Using EOF Analysis and Multivariate Linear Regression
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A popular approach for empirical modeling is through representing a phenomenon as a linear combination of a set of predefined basis functions, such as polynomial and harmonic functions. In comparison with predefined basis functions, the empirical orthogonal basis functions (EOFs) are constructed from the dataset according to the variance distribution, and typically summarize the data into representative features. This chapter reviews comparatively three applications of EOF analysis associated with multivariate linear regression in empirical modeling, namely in the models of the Earth’s ionospheric F 2 -layer peak, the field-aligned currents at Earth, and the induced magnetic field near Venus (He et al. Geophys. Res. Lett., 38(14): L14101, 2011; He et al. Geophys. Res. Lett., 39, 2012; He et al. 2017; He et al. J. Geophys. Res., 121(4), 3362–3380, 2016). We illustrate the physical meaning represented by the most important EOFs, detail the model constructions and methodology, and highlight the revealed main scientific results.
The authors acknowledge the online services provided by NASA’s Planetary Data System (MESSENGER data), ESA’s Planetary Science Archive (VEX data), GFZ Potsdam (CHAMP data), NGDC (POMME-6.2 coefficients), John Hopkins University APL (AACGM coefficients), and NASA OMNI (IMF/SW and other geophysical parameters). The corresponding codes are available on Source Forge or File change of MATLAB Central. This work was supported by the Deutsche Forschungsgemeinschaft through grants DFG HE6915/1-1 and VO 855/3-1.
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