An Investigation of the Global TEC Behavior from 1999 to 2017 Variations and Deviations

Geomagnetism and Aeronomy - The global TEC (Total Electron Content) behavior has been studied for several decades, but some properties of this behavior have not been understood well, such as the...     

Using of gene expression programming and climatic data for forecasting flow discharge by considering trend,normality, and stationarity analysis

In this research, the main hydrological characteristics (such as trend, stationarity, and normalization of hydrological data) of the Kasilian watershed are considered from 1970 to 2009. For forecasting of discharge, gene expression programming (GEP) method is applied. Normality and stationarity of time series are necessary for application of GEP method. For this purpose, third edition of Mann-Kendall trend test and skewness test are used for detection of trend and normalization of data, respectively. Also, five methods are applied for detection of stationarity of data. Modified Mann-Kendall trend test and Theil and Sen’s median slope method illustrate that annual and monthly precipitation data have slight decreasing trend, annual and monthly discharge data have insignificant decreasing trend, and annual and monthly temperature data have an increasing trend. Skewness test illustrates that annual, monthly, and daily discharge and precipitation data are not normal. By using logarithm function, skewness is minimized and symmetry of data is improved. After normalization of time series by logarithm function, five methods are applied for testing of stationarity of time series. These methods show that different normalized time series are stationarity and stationarity of time series is improved by elimination of periodic properties of data. For forecasting of daily discharge by GEP method, 85% of data are used for training and 15% of data are used for testing. By using data of 3 days ago, the GEP has the best efficiency. Coefficient of correlation (CC), root mean square error (RMSE), mean absolute error (MAE), and mean absolute relative error (MARE) are 0.9, 0.495 lit/s, 0.288 lit/s, and 0.053, respectively.     

A Simulation Study of the Plasma Wave Enhancements in the Earth’s Equatorial Plasmasphere

In the equatorial plasmasphere, plasma waves are frequently observed. To improve our understanding of the mechanism generating plasma waves from instabilities, a comparison of observations, linear growth-rate calculations, and simulation results is presented. To start the numerical experiments from realistic initial plasma conditions, we use the initial parameters inferred from observational data obtained around the plasma-wave generation region by the Akebono satellite. The linear growth rates of waves of different modes are calculated under resonance conditions, and compared with simulation results and observations. By employing numerical experiments by a particle code, we first show that upper hybrid-, Z-, and whistler-mode waves are excited through instabilities driven by a ring-type velocity distribution. The simulation results suggest a possibility that energetic electrons with energies of some tens of keV confined around the geomagnetic equator are responsible for the observed enhancements of Z- and whistler-mode waves. While the comparison between linear growth-rate calculations and observations shows the different tendency of wave amplitude of Z-mode and whistler-mode waves, the wave amplitude of these wave modes in the simulation results is consistent with the observation.