Taiwan Ionospheric Model (TWIM) prediction based on time series autoregressive analysis

L. C. Tsai, Ernest P. Macalalad, C. H. Liu

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

As described in a previous paper, a three-dimensional ionospheric electron density (Ne) model has been constructed from vertical Ne profiles retrieved from the FormoSat3/Constellation Observing System for Meteorology, Ionosphere, and Climate GPS radio occultation measurements and worldwide ionosonde foF2 and foE data and named the TaiWan Ionospheric Model (TWIM). The TWIM exhibits vertically fitted α-Chapman-type layers with distinct F2, F1, E, and D layers, and surface spherical harmonic approaches for the fitted layer parameters including peak density, peak density height, and scale height. To improve the TWIM into a real-time model, we have developed a time series autoregressive model to forecast short-term TWIM coefficients. The time series of TWIM coefficients are considered as realizations of stationary stochastic processes within a processing window of 30 days. These autocorrelation coefficients are used to derive the autoregressive parameters and then forecast the TWIM coefficients, based on the least squares method and Lagrange multiplier technique. The forecast root-mean-square relative TWIM coefficient errors are generally <30% for 1 day predictions. The forecast TWIM values of foE and foF2 values are also compared and evaluated using worldwide ionosonde data.

Original languageEnglish
Pages (from-to)977-986
Number of pages10
JournalRadio Science
Volume49
Issue number10
DOIs
StatePublished - 1 Oct 2014

Keywords

  • autoregressive analysis
  • ionospheric electron density model
  • ionospheric prediction

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