Modeling the global ionospheric variations based on complex network

Abstract

The modern science of networks has brought significant advances to our understanding of complex systems. We employ the probabilistic graphical model to build complex networks to model the global ionospheric variations. The global ionospheric maps (GIMs) of vertical total electron content (VTEC) for the 12 months in 2012 have been selected analyze the ionospheric variations from the perspective of complex network. The information flow in the networks represents the causal interactions between the ionospheric variations at different locations. The distributions of the edges' geospatial distances in the ionospheric networks show that the information flow in the ionosphere is mainly transmitted locally, almost obeying the geospatial proximity principle. The asymmetric distribution of the edges' distances probably elucidates the more efficient transmission of ionospheric variations in the westward and southward directions. The community topologies within the ionospheric networks indicate the effect of the geomagnetic field and geographical distance on the information flow in the ionosphere. The geomagnetic field has shown an enhanced effect on the meridional interaction in the ionosphere, causing the vertical community topologies within the ionospheric networks at middle and low latitudes. For the ionospheric cells located at high latitudes in GIM, the geographical distances result in the horizontal community topologies. The fractal analysis reveals the existence of self-similar structure in the ionospheric networks on the global scale. The fractality in the ionospheric information flow may indicate the reasonability of the VTEC's prediction at a certain location by spatial prediction based on the data obtained in known regions.