Time series autoregression technique implemented on-line in DIAS system for ionospheric forecast over EuropeK. Koutroumbas, I. Tsagouri, and A. BelehakiNational Observatory of Athens, Institute for Space Applications and Remote Sensing, Greece
Abstract. A new method for ionospheric predictions based on time series autoregressive
models (AR) that was recently developed to serve the needs of the European
Digital Upper Atmosphere Server (DIAS) for short term forecast of the foF2
parameter over Europe (up to the next 24 h) is described. Its
performance for various steps ahead is compared with the outcome of neural
network predictors for both storm and quiet periods in two DIAS locations,
Athens and Pruhonice. The results indicate that the proposed method provides
robust short term forecasts of the foF2 for the middle latitude ionosphere.
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Citation: Koutroumbas, K., Tsagouri, I., and Belehaki, A.: Time series autoregression technique implemented on-line in DIAS system for ionospheric forecast over Europe, Ann. Geophys., 26, 371-386, 2008. Bibtex EndNote Reference Manager