Modeling Chinese ionospheric layer parameters based on EOF analysis

Abstract

Using 24-ionosonde observations in and around China during the 20th solar cycle, an assimilative model is constructed to map the ionospheric layer parameters (f o F 2 , h m F 2 , M(3000)F 2 , and f o E) over China based on empirical orthogonal function (EOF) analysis. First, we decompose the background maps from the International Reference Ionosphere model 2007 (IRI-07) into different EOF modes. The obtained EOF modes consist of two factors: the EOF patterns and the corresponding EOF amplitudes. These two factors individually reflect the spatial distributions (e.g., the latitudinal dependence such as the equatorial ionization anomaly structure and the longitude structure with east-west difference) and temporal variations on different time scales (e.g., solar cycle, annual, semiannual, and diurnal variations) of the layer parameters. Then, the EOF patterns and long-term observations of ionosondes are assimilated to get the observed EOF amplitudes, which are further used to construct the Chinese Ionospheric Maps (CIMs) of the layer parameters. In contrast with the IRI-07 model, the mapped CIMs successfully capture the inherent temporal and spatial variations of the ionospheric layer parameters. Finally, comparison of the modeled (EOF and IRI-07 model) and observed values reveals that the EOF model reproduces the observation with smaller root-mean-square errors and higher linear correlation coefficients. In addition, IRI discrepancy at the low latitude especially for f o F 2 is effectively removed by EOF model.

α‐Chapman Scale Height: Longitudinal Variation and Global Modeling

“…Further details about PCA can be found in the tutorial by Smith (). Since PCA was first introduced into the field of meteorology by Lorenz (), it has been frequently used in data analyses and modelings of ionosphere and atmosphere (Chen et al, ; Le et al, ; Lei et al, ; Natali & Meza, ; She et al, ; Talaat & Zhu, ; Y. Yu et al, ; S.‐R. Zhang et al, ).…”

Equatorial ionization anomaly in the low‐latitude topside ionosphere: Local time evolution and longitudinal difference

“…EOF analysis has been widely used for analyzing the spatial and temporal variations of geophysical fields since it was introduced into meteorology by Lorenz []. EOF analysis was also successfully applied to ionospheric data analyses and empirical modeling [e.g., Daniell et al , ; Dvinskikh , ; Singer and Taubenheim , ; W. X. Wan et al , ; Yu et al , ; Zapfe et al , ; Zhang et al , ; Zhao et al , ]. In this study, we applied EOF analysis to topside N i to decompose the data into a series of eigenmodes of N i versus longitude and latitude (EOF eigenfunctions) and their associated coefficients (EOF coefficients).…”

“…EOF analysis was also successfully applied to ionospheric data analyses and empirical modeling [e.g., Daniell et al, 1995;Dvinskikh, 1988;Singer and Taubenheim, 1990; W. X. Yu et al, 2015;Zapfe et al, 2006;Zhang et al, 2009b;Zhao et al, 2005]. In this study, we applied EOF analysis to topside N i to decompose the data into a series of eigenmodes of N i versus longitude and latitude (EOF eigenfunctions) and their associated coefficients (EOF coefficients).…”

New understanding achieved from 2 years of Chinese ionospheric investigations

“…Yu et al [81] constructed the maps of the ionospheric layer parameters (foF2, hmF2, M(3000)F2, and foE) over China based on an EOF analysis using the 20th solar cycle observations from 24-ionosonde in Asia. They decomposed the EOF modes from the IRI-07, assimilated the EOF patterns to get information on the amplitudes from ionosonde observations, which is further used to construct the Chinese ionospheric maps (CIMs) of the layer parameters.…”