• Title of article

    The Direct and Indirect Methods of Ionospheric TEC Predictions and Their Comparison

  • Author/Authors

    Li، نويسنده , , Zhi-Gang and Li، نويسنده , , Weichao and Cheng، نويسنده , , Zong-Yi and Feng، نويسنده , , Chu-Gang، نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 2008
  • Pages
    16
  • From page
    277
  • To page
    292
  • Abstract
    The direct and indirect methods for predicting the ionospheric total electron content (TEC) by using the ARIMA (p, d, q) model in the theory of time-series analysis are proposed. The direct method predicts directly the time series composed of the TECs at the every grid point. The indirect method is: at first, to fit the ionospheric TECs with the spherical harmonics and obtain the time series of the fitting coefficients; then, to predict forward the fitting coefficients with the ARIMA (p, d, q) model in the theory of time-series analysis; and finally, to calculate the TEC for the specific time and grid point. Using the ionospheric data of the International GPS Service (IGS) in the period from 1 January 2004 to 31 January 2005, the testing and comparisons on the proposed methods are performed, the results indicate that within 12 days, the results of the two methods are basically consistent, and that for the predictions longer than 12 days, the accuracy of the indirect method is higher than the direct method. In the duration of 20 days, relative to the total ionospheric grid points, the percentage of the grid points with a prediction error less than 3 TECUs is about 80%; as the duration becomes longer, compared with the indirect method, the decline of this percentage is not apparent for the direct method. Obviously, the direct method suits the prediction of regional TECs, and the indirect method suits the prediction of global TECs.
  • Keywords
    Earth: ionosphere , method: data analysis
  • Journal title
    Chinese Astronomy and Astrophysics
  • Serial Year
    2008
  • Journal title
    Chinese Astronomy and Astrophysics
  • Record number

    2263782