Regional reference total electron content model over Japan based on neural network mapping techniques

Abstract

Abstract.A regional reference model of total electron content (TEC) was constructed using data from the GPS Earth Observation Network (GEONET), which consists of more than 1000 Global Positioning System (GPS) satellite receivers distributed over Japan. The data covered almost one solar activity period from April 1997 to June 2007. First, TECs were determined for 32 grid points, expanding from 27 to 45 • N in latitude and from 127 to 145 • E in longitude at 15-min intervals. Secondly, the time-latitude variation averaged over three days was determined by using the surface harmonic functional expansion. The coefficients of the expansion were then modeled by using a neural network technique with input parameters of the season (day of the year) and solar activity (F10.7 index and sunspot number). Thus, two-dimensional TEC maps (time vs. latitude) can be obtained for any given set of solar activity and day of the year.

TEC prediction with neural network for equatorial latitude station in Thailand

“…NN is an important tool for nonlinear approximation when it is trained with sufficient historic data (Habarulema et al, 2007). TEC is one of the nonlinear ionospheric parameters which have been previously predicted by using NN (Habarulema et al, 2007(Habarulema et al, , 2009aMaruyama, 2007;Watthanasangmechai et al, 2010). Among the various NN structures, we have used a basic structure known as a feed-forward network with a back propagation algorithm, the well-known algorithm, for our model.…”

“…Neural network (NN) techniques have been applied to various topics in the study of the upper atmosphere. A number of works employ the NN to predict atmospheric parameters and determine the optimum parameters for modeling, such as the temporal and spatial forecasting of the f o F 2 values up to twenty-four hours in advance and near-real time prediction (Tulunay et al, 2000;Oyeyemi et al, 2006), to make operational forecasts of ionospheric variations (Nakamura et al, 2007), the topside ionospheric variability and electron-density modelling (McKinnell and Poole, 2001;Maruyama, 2002), solar proxies pertaining to an empirical model (McKinnell, 2008;Maruyama, 2010), and regional TEC modeling with the NN (Leandro and Santos, 2004;Tulunay et al, 2004b;Maruyama, 2007;Habarulema et al, 2007Habarulema et al, , 2009b; Watthanasangmechai et al, 2010).…”

First results from the ionospheric tomography experiment using beacon TEC data obtained by means of a network along a longitude of 136°E over Japan

“…This is the signature of the mid-latitude summer nighttime anomaly (MSNA) reported by Lin et al (2009). The evening time enhancement of TEC in the summer season over Japan has also reported by Maruyama (2007) using GPS TEC measurements. The MSNA can be described as a state in which the nighttime plasma density at the mid-latitude region exceeds the daytime values, and the density at the northern mid-latitudes (> ∼33-34 • N) often remains higher than that at latitudes of less than ∼33…”

Comparison of the Kriging and neural network methods for modeling foF2 maps over North China region

“…Recently, Leandro and Santos (2007) developed a total electron content (TEC) regional model for the Brazilian using the NN method. Maruyama (2008) developed a regional reference TEC model over Japan using the NN technique. Yilmaz et al (2009) used the NN method to develop a regional TEC mapping model over central Europe.…”