Abstract
Total Electron Content (TEC) is an important characteristic of the ionosphere relevant to communications. Unpredictable variability of the ionospheric parameters due to various disturbances limits the efficiencies of communications, radar and navigation systems. Therefore forecasting and nowcasting of TEC are important in the planning and operation of Earth-space and satellite-to-satellite communication systems. Near-Earth space processes are complex being highly nonlinear and time varying with random variations in parameters where mathematical modeling is extremely difficult if not impossible. Therefore data driven models such as Neural Network (NN) based models are considered and found promising in modeling such processes. In this paper the NN based METU-NN model is introduced to forecast TEC values for the intervals ranging from 1 to 24 h in advance. Forecast and nowcast of TEC values are also considered based on TEC database. Day-to-day and hour to-hour variability of TEC are also estimated using statistical methods. Another statistical approach based on the clustering technique is developed and a preprocessing approach is demonstrated for the forecast of ionospheric critical frequency foF2.
Highlights
16.1. INTRODUCTIONUnpredictable variability of ionospheric parameters due to disturbances related to the ionosphereplasmapause system limits the efficiency of HF and other communications, radar and navigation systems by causing serious technological problems including range errors, rapid phase and amplitude fluctuations, in other words, radio scintillations of satellite signals and others
Unpredictable variability of ionospheric parameters due to disturbances related to the ionosphereplasmapause system limits the efficiency of HF and other communications, radar and navigation systems by causing serious technological problems including range errors, rapid phase and amplitude fluctuations, in other words, radio scintillations of satellite signals and others.With the future advancement of technology, the above-mentioned risks and financial losses will certainly increase unless swift measures are taken in advance
Day-to-day and hour-to-hour variabilities of Total Electron Content (TEC) are estimated using statistical methods. Another statistical approach which is based on the clustering technique is developed and a processing approach is demonstrated for the forecast of foF2
Summary
Unpredictable variability of ionospheric parameters due to disturbances related to the ionosphereplasmapause system limits the efficiency of HF and other communications, radar and navigation systems by causing serious technological problems including range errors, rapid phase and amplitude fluctuations, in other words, radio scintillations of satellite signals and others. The NN based Middle East Technical University METU-NN model is introduced to forecast the 10 min TEC variations during the high solar activity in the current solar cycle for the intervals ranging from 1 to h in advance by running the model in RAL using RAL data. Day-to-day and hour-to-hour variabilities of TEC are estimated using statistical methods Another statistical approach which is based on the clustering technique is developed and a processing approach is demonstrated for the forecast of foF2
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