Spatial and temporal variation of total electron content as revealed by principal component analysis

Elsayed R Talaat,Xun Zhu

doi:10.5194/angeo-34-1109-2016

Abstract

Abstract. Eleven years of global total electron content (TEC) data derived from the assimilated thermosphere–ionosphere electrodynamics general circulation model are analyzed using empirical orthogonal function (EOF) decomposition and the corresponding principal component analysis (PCA) technique. For the daily averaged TEC field, the first EOF explains more than 89 % and the first four EOFs explain more than 98 % of the total variance of the TEC field, indicating an effective data compression and clear separation of different physical processes. The effectiveness of the PCA technique for TEC is nearly insensitive to the horizontal resolution and the length of the data records. When the PCA is applied to global TEC including local-time variations, the rich spatial and temporal variations of field can be represented by the first three EOFs that explain 88 % of the total variance. The spectral analysis of the time series of the EOF coefficients reveals how different mechanisms such as solar flux variation, change in the orbital declination, nonlinear mode coupling and geomagnetic activity are separated and expressed in different EOFs. This work demonstrates the usefulness of using the PCA technique to assimilate and monitor the global TEC field.

Highlights

The ionosphere is highly variable and has a complex system of drivers including variable solar radiation plus geomagnetic activity from the upper atmosphere and momentum and energy fluxes associated with neutral wind dynamics from the lower atmosphere
To further demonstrate the benefit of the principal component analysis (PCA) technique in the current application, we show in Fig. 10 the time series of the longitudinally averaged total electron content (TEC) in the unit of www.ann-geophys.net/34/1109/2016/
When PCA is coupled with the spectral analysis of the time series of the empirical orthogonal function (EOF) coefficients, it is shown that the EOF analysis is a data compression technique and a powerful tool to objectively reveal the relative importance of individual physical mechanisms that are responsible for the total TEC variance

Summary

Introduction

The ionosphere is highly variable and has a complex system of drivers including variable solar radiation plus geomagnetic activity from the upper atmosphere and momentum and energy fluxes associated with neutral wind dynamics from the lower atmosphere. The ionosphere varies on all these timescales in response to the solar inputs, while the geographic relationship of the Earth’s orbit, rotation and seasonal tilt creates the solar zenith angle dependence that yields the observed diurnal, seasonal and annual variations in ionospheric density. This is further complicated by the tilt of the magnetic field of Earth, the magnetospheric inputs that drive the ionosphere at high latitudes, and the neutral dynamics generated by solar and magnetospheric forcing, indicating significant longitudinal and hemispherical asymmetries in space.

A brief review and notations of the EOF and PCA

EOF and PCA applied to daily averaged TEC

EOF and PCA applied to hourly TEC

Physical processes as objectively revealed by EOFs and TEC

Findings

Summary and conclusions