Investigating the effect of the removing well-known periods from TEC time series data in identifying seismo-ionospheric anomaly

Iran is situated on one of the two largest seismic belt of the world which is called Alpa. The occurrence of damaging earthquakes all around the country causes a lot of pecuniary losses and casualties. The prediction of this phenomenon can have a profound impact on reducing the risks which are posed by it. Among the earthquake predictors, which are of interest to many scholars today, we can mention the occurrence of abnormal changes in the ionospheric parameters. The studied ionospheric parameter in this paper is the Total Electron density Content (TEC) obtained from the Global Inosphere Map (GIM). The time series of the TEC data comprises well-known periods whose causes are not seismic. It seems that, by eliminating the effect of these factors, as much as possible, the identification of the ionospheric-seismic anomaly could be done much more accurately. In this study, changes in TEC before the occurrence of two earthquakes in Iran have been investigated by using the mean method two times, once before the elimination of the periods and once afterwards.  In fact, after the removal of known frequencies for Khuzestan and Semnan earthquakes in the area of identification of seismo-ionospheric anamolysis, the improvement of more than 50% and  10%   is seen in most of the places respectively.