As the fact that most of the ground-based GPS lacks of the detection of the upper-air meteorological data, thus the application of ground-based GPS sensing of water vapor technology has been limited due to the inaccurately calculated weighted mean temperature. In that case, this paper has studied and analyzed the methods of obtaining weighted mean temperature by deriving the data from GGOS Atmosphere weighted mean temperature grid data in Xinjiang. By using the radiosonde data, this paper has evaluated the accuracy of the weighted mean temperature(GTm) derived from GGOS atmosphere weighted mean temperature grid data and considering the seasonal and geographic factors , we employed a correction model to fit the residuals of GTm. Results show that the GTm derived from mean value interpolation and corrected by correction model meet the requirements of ground-based GPS precision sensing of Water Vapor in Xinjiang ; The inner average precision RMSD is 2.33K , MAE is 1.80 K; The outer average precision RMSD is 2.36K , MAE is 1.85 K.
Klobuchar model can reflect the spatial and temporal variations of ionospheric feature, but model fixed initial phase and night-time delay will introduce a large number of errors. Aiming at the shortcomings of the models, take least-squares surface fitting model as the background, using CORS network in Nanning region to measure the data correctly, the Klobuchar model's initial phase, amplitude, and night-time delay values are steadily corrected, so as to establish regional ionospheric model in Nanning, the results show that the accuracy of Klobuchar model is improved significantly.
Aiming at the characteristic of nonlinear and non-stationary in ionospheric total electron content(TEC), this article bring Wavelet Analysis into the autoregressive integrated moving average model to forecast the next four days’ TEC values by using six days’ ionospheric grid observation data of Chinese area in 2010 provided by IGS station. Taking IGS station’s observation data as true value, compare the forecast value with it then count the forecast accuracies which are to prove that it has a quite good result by using WARIMA model to forecast Chinese area’s Ionospheric grid data. But near the geomagnetic latitude of about ±20°grid, the model’s forecast results are a little worse than others’ because Geomagnetic activity is irregular which lead to the TEC values there change greatly.
The formation of the ionosphere is mainly the interaction of solar radiation and the earth's atmosphere, in different
temporal-spatial environment, the characteristics of the ionosphere is more complex, and the Total Electron Content
(TEC) is one of the important parameters of the ionospheric morphology and structure. Therefore, in this paper, using the
high-precision TEC time series provided by the International GNSS Service (IGS) as experimental data, by Fast Fourier
Transform (FFT) to detect its periodic changes, and then focus on analysis the characteristics of diurnal variation,
seasonal variation and annual variation and winter anomaly, simultaneous analysis of the ionospheric characteristics vary
with latitude and longitude. The result show that: (1) TEC changes more intense during the day, but the night is quiet,
and in different latitudes, the TEC reached peak value at different moment; (2) Winter anomaly exists only during the day,
night does not exist; (3) In the same time domain, TEC value decreases gradually with the increase of latitude, and it has
different spatial variation features in different hemispheres.