Modeling of ionospheric irregularities in the Arctic region based on empirical orthogonal function method

The polar ionosphere is often highly structured with significant plasma irregularities, influencing the Global Navigation Satellite System (GNSS) service that relies on trans-ionospheric radio waves. Due to the practical usage, there is a high demand for modeling and forecasting of ionospheric irregularities. In this study, we develop a climatological model based on the long-term dataset (2010-2021) of rate of change of the total electron content (TEC) index (ROTI) maps from the International GNSS Service (IGS). The IGS ROTI maps are daily averaged in magnetic coordinates. In order to develop a climatological model, the ROTI maps are decomposed into a few base functions and coefficients using the empirical orthogonal function (EOF) method. The EOF method converges very quickly, and the first four EOFs could reflect the majority (96%) of the total data variability. Furthermore, the first four EOF base functions reflect different drivers of ionospheric irregularities. For example, the first EOF reflects the averaged ROTI activity and the impact of the solar radiation characterized by F10.7; the 2^nd EOF base function reflects the impact of interplanetary magnetic field (IMF) Bz and electric field; the 3^rd and 4^th EOF base functions reflect the dawn-dusk asymmetry in the auroral oval and polar cap, and therefore related to the IMF By. To build an empirical model, we fit the EOF coefficients using geophysical proxies from four different categories (namely, solar radiation, magnetic indices, IMF, and solar wind coupling function) based on linear regression. The preliminary data-model comparison shows satisfactory results with a good correlation coefficient and adequate errors.