The influence of ionospheric thin shell height on TEC retrieval from GPS observation

We investigate the influence of assumed height for the thin shell ionosphere model on the Total Electron Content（TEC） derived from a small scale Global Positioning System（GPS） network. TEC and instrumental bias are determined by applying a grid-based algorithm to the data on several geomagnetically quiet days covering a 10 month period in 2006. Comparisons of TEC and instrumental bias are made among assumed heights from 250 km to 700 km with an interval of 10 km. While the TEC variations with time follow the same trend, TEC tends to increase with the height of the thin shell. The difference in TEC between heights 250 km and 700 km can be as large as～8 TECU in both daytime and nighttime. The times at which the TEC reaches its peak or valley do not vary much with the assumed heights. The instrumental biases, especially bias from the satellite, can vary irregularly with assumed height. Several satellites show a large deviation of～3 ns for heights larger than 550 km. The goodness of fit for different assumed heights is also examined. The data can be generally well-fitted for heights from 350 km to 700 km. A large deviation happens at heights lower than 350 km. Using the grid-based algorithm, there is no consensus on assumed height as related to data fitting. A thin shell height in the range 350-500 km can be a reasonable compromise between data fitting and peak height of the ionosphere.

An Improved Extreme Learning Machine Prediction Model for Ionospheric Total Electron Content

Earth’s ionosphere is an important medium for navigation,communication,and radio wave transmission.Total Electron Content(TEC)is a descriptive quantify for ionospheric research.However,the traditional empirical model could not fully consider the changes of TEC time series,the prediction accuracy level of TEC data performed not high.In this study,an improved Extreme Learning Machine(ELM)model is proposed for ionospheric TEC prediction.Improvements involved the use of Empirical Mode Decomposition(EMD)and a Fuzzy C-Means(FCM)clustering algorithm to pre-process data used as input to the ELM model.The proposed model fully uses the TEC data characteristics and expected to perform better prediction accuracy.TEC measurements provided by the Centre for Orbit Determination in Europe(CODE)were used to evaluate the performance of the improved ELM model in terms of prediction accuracy,applicable latitude,and the number of required training samples.Experimental results produced a Mean Relative Error(MRE)and a Root Mean Square Error(RMSE)of 8.5%and 1.39 TECU,respectively,outperforming the ELM algorithm(RMSE=2.33 TECU and MRE=17.1%).The improved ELM model exhibited particularly high prediction accuracy in mid-latitude regions,with a mean relative error of 7.6%.This value improved further as the number of available training data increased and when 20-doys data were trained,achieving a mean relative error of 4.9%.These results suggest the proposed model offers higher prediction accuracy than conventional algorithms.

GPS-based regional ionospheric models and their suitability in Antarctica

There are a number of ionospheric models available for research and application, such as the polynomial model, generalized trigonometric series function model, low degree spherical harmonic function model, adjusted spherical harmonic function model, and spherical cap harmonic function analysis. Using observations from more than 40 continuously operating stations across Antarctica in 2010, ifve models are compared with regard to their precision and applicability to polar regions. The results show that all the models perform well in Antarctica with 0.1 TECU of residual mean value and 2 TECU of root mean square error.

Analysis of ionospheric anomaly preceding the Mw7.3 Yutian earthquake

On February 12,2014,a large Mw7. 3 earthquake occurred in Yutian of Xijiang Province,China.We processed the global ionosphere maps provided by CODE（ the Center for Orbit Determination in Europe）and the foF2（ the critical frequency of F2-layer） data of Chongqing ionosonde station to analyze the preearthquake ionospheric anomalies. Solar activities and magnetic storm were checked by the sliding inter quartile range method to remove their effects on the ionosphere. A positive ionospheric anomaly with the large amplitude of 20 TECU was observed near the epicenter on February 3（ 10th day before the earthquake）. In addition,the foF2 at Chongqing station had an unusual increase of more than 40% on the day,which was consistent with the TEC（ Total Electron Content） anomaly. The global disturbance represents that the peak of TEC anomaly didn’t coincide with the vertical projection of epicenter. The TEC anomalous area was closer to the equator,and it mainly occurred from local time 16 ∶ 00 to 20 ∶ 00. An enhancement of TEC with the small amplitude also appeared in the magnetically conjugated region.

Ionospheric disturbances associated with the 2015 M7.8 Nepal earthquake

Based on the total electron content （TEC） derived from Global Positioning System （GPS） observations of the Crustal Movement Observation Network of China （CMONOC） and the Global Ionosphere Map （GIM） from the Center for Orbit Determination in Europe （CODE）, we detected and analyzed the ionospheric variations during the 2015 M7.8 Nepal earthquake （including the pre-earthquake ionospheric anomalies and coseismic ionospheric disturbances （CIDs） following the main shock）. The analysis of vertical total electron content （VTEC） time series shows that the large-scale ionospheric anomalies appeared near the epicenter two days prior to the earthquake. Moreover, the pre-earthcluake ionospheric anomalies were also observed in the geomagnetically conjugated region. In view of solar-terrestrial environment, the pre-earthquake ionospheric anomalies could be associated with the Nepal earthquake. In addition, we also detected the CIDs through the high-frequency GPS observation stations. The CIDs had obvious oscillated waveforms with the peak-to-peak disturbance amplitudes of about I TECu and 0.4 TECu, which propagated approximately with the horizontal velocities of 877 ±75 m/s and 319 ± 30 m/s, respectively. The former is triggered directly by the acoustic waves which originated from the energy release of the earthquake near the epicenter, while the latter could be stimulated by the acoustic-gravity waves from the partial transformation of the acoustic waves.

Spectral investigation of traveling ionospheric disturbances:IONOLAB-FFT

Ionosphere is an important layer of atmosphere which is under constant forcing from both below due to gravitational, geomagnetic and seismic activities, and above due to solar wind and galactic radiation. Spatio-temporal variability of ionosphere is made up of two major components that can be listed as spatio-temporal trends and secondary variabilities that are due to disturbances in the geomagnetic field, gravitational waves and coupling of seismic activities into the upper atmosphere and ionosphere. Some of these second order variabilities generate wave-like oscillations in the ionosphere which propagate at a certain frequency, duration and velocity. These oscillations cause major problems for navigation and guidance systems that utilize GNSS （Global Navigation Satellite Systems）. In this study, the frequency and duration of wave-like oscillations are determined using a DFT （Discrete Fourier Transform） based algo- rithm over the STEC （slant total electron content） values estimated from single GPS （Global Positioning System） station. The performance of the developed method, namely IONOLAB-FFT, is first determined using synthetic oscillations with known frequencies and durations. Then, IONOLAB-FFr is applied to STEC data from various midlatitude GPS stations for detection of frequency and duration of both medium and large scale TIDs （traveling ionospheric disturbances）. It is observed that IONOLAB-FFr can estimate TIDs with more than 80% accuracy for the following cases： frequencies from 0.6 mHz to 2.4 mHz and durations longer than 10 min; frequencies from 0.15 mHz to 0.6 mHz and durations longer than 50 min; fre- quencies higher than 0.29 mHz and durations longer than 50 rain.