Accuracy Estimation of the Modern Core Magnetic Field Models Using DMA-Methods for Recognition of the Decreased Geomagnetic Activity in Magnetic Observatory Data

Abstract

A new approach to identify the signals of the Earth’s main magnetic field (core field) based on the magnetic observatory data processing is suggested. The algorithms implemented in the approach are based on the Discrete mathematical analysis (DMA). The developed method is used to analyze the data from 49 midand low-latitude observatories of the INTERMAGNET network collected in 2011–2015. The results are compared with the classical method for determining the periods of low magnetic activity of external origin which is adopted by the International Association for Geomagnetism and Aeronomy (IAGA). The advantages of the suggested new approach are demonstrated. Based on the data records for the selected time intervals, the time series of the core field components and their secular variations are obtained for each observatory. These data are compared to the values predicted by the most accurate core field models: SIFM, CHAOS-6, and EMM-2015. The accuracy of the models is estimated using a set of statistical parameters: Pearson’s coefficient of linear correlation, Spearman’s and Kendall’s coefficients of rank correlation, the mean and median values over the data sets, and the mean difference between the data obtained by the suggested method from observatory measurements and the model predictions.