Global ionospheric maps forecasting based on an adaptive autoregressive modeling of grid point VTEC values

Abstract

In the context of the International GNSS Service (IGS), the Ionosphere Associate Analysis Centers (IAACs) generate daily global ionospheric maps (GIMs). Time delays of at least one day for the daily GIMs product limit its value in real-time GNSS applications requiring high precision. Short-time forecasting of GIMs would be a good way to provide a basic background model for single-frequency GNSS users. We propose an improved algorithm for GIMs forecasting based on an adaptive autoregressive (AR) modeling of grid point vertical total electron content (VTEC) values (TVPG). We compare final daily GIMs (BUAG) with precise point positioning (PPP) derived VTEC values (PPPG) and JASON-2 VTEC values (J2TEC) to evaluate the performance of the TVPG and the GIMs based on the prediction of spherical harmonics coefficients (SHPG). The results of the comparison indicate that the TVPG have no obvious overestimate or underestimate with respect to BUAG. While, SHPG overestimates VTEC values in northern latitudes, and underestimates VTEC values in southern latitudes, by more than 2 TECU in some latitudes. Also, according to a comparison with PPPG and J2TEC, the TVPG is essentially better than the SHPG in middle and high latitudes at both low and high solar activity. However, it is worthy of further study to improve the performance of forecast GIMs in low latitudes.