Study On The Ionospheric TEC Storm And Its Forecasting Method

Ionospheric storm is an important space weather phenomenon, and it also is an important research task in space physics in nowadays. Because the value of ionospheric parameters (as TEC and foF2etc) during storm-time greatly deviate the value of background, it will bring more severe propagation effects to the radio information system as communication, navigation, radar, survey and control and etc. Especially, for these systems that radiowave propagates through ionosphere, many propagation effects are directly related to the value of TEC. So, it has the important scientific significance and the wide applied outlook to study the ionospheric TEC storm and its forecasting method.In this thesis, we summarize the fast development of GPS-TEC measurement technique and the research progressing of ionospheric storm, and exploringly study the TEC storm and its forecasting method based on the observations of ionospheric TEC in China and its surrounding area. And these preliminary study results are presented as follows:1. Put forward the quantitative criteria for to identify the TEC storm event. Firstly, an ionospheric TEC disturbance index (DI) is introduced, and it is the relative deviation of TEC. Secondly, the variation of the upper and lower5%values of DI are investigated including the diurnal variations, the seasonal variations, the latitudinal variation and the solar activity variations in six GPS monitoring sites in China. Thirdly, the criteria of the positive (negative) TEC disturbance state are determine according as DI>0.35(DI≤-0.30). Lastly, the positive (or negative) ionospheric TEC storm event is identified when the DI values at six consecutive hours exceeds above level.2. Analyzed the disturbed characters of TEC storm event in China area. Some characters of the TEC storm event are obtained by statistical analysis including the occurrence peak of local time, the average duration, the storm phase changes with the seasons and the geographic latitudes. And other characters are also fund by a case study including the latitudinal response, the spatial relativity, and the perturbation propagation.3. Discussed the relativity between the TEC storm and the disturbances of solar-terrestrial conditions. By the statistical method, we quantitatively evaluate the relationship between the occurrence of TEC storm events and these factors including the solar flares and its flux, the IMF-Bz and its change rate, the geomagnetic storm, and the typhoon.4. Seek after the forecasting method of ionospheric TEC storm. The artificial Neural Networks (NNs) is used considering the non-linear effects of these parameters during storm. And the prediction thought of TEC storm is performed from two aspects, includes the occurrence of TEC storm events and the TEC variation during storm. And the latter is divided into the single-station forecasting and the region reconstruction again.4.1Developed a short-term forecasting method of the occurrence of ionospheric TEC storm event. A NNs is designed, which inputs include these information from the solar flare, the IMF, the solar wind, the geomagnetic storm, the season and the local time, and output is a set token parameters of TEC storm event. Results show the method can effectively forecast the occurrence of TEC storm event in24h, and its accuracy is up to94.3%.4.2Developed the single-site short-term forecasting methods of TEC during storm-time for the positive and the negative storm respectively. The NNs is designed, which inputs include five sorts’data as the foregone TEC, the F10.7, the Ap, the season, and the local time, and output is the TEC value of the prediction time. Results show these methods can forecast the TEC value during storm-time in advanced from1h to24h. And the error analysis shows they have better accuracy for both positive and negative storm.4.3Developed a region reconstruction method of TEC during storm-time. A NNs is designed, which inputs include five sorts’data as the TEC values from multi-site in certain region, the Ap, the geographic coordinates of reconstruction site, the season, and the local time, and which output is the TEC value of reconstruction site. Results show the method can effectively reconstruct the TEC map, and its accuracy is better than the Kriging method.