Highlights Global median empirical model of GTEC is developed based on GIM-TECs for 1996–2019. Spherical Harmonic latitude and longitude functions with associated numerical coefficients. GTEC improves IRI-Plas TEC predictions about 2 times compared to Ne(h) integration.

    Abstract Global median empirical model of Total Electron Content (GTEC) is developed driven by re-calibrated sunspot numbers, SSN2, for the quiet geomagnetic conditions (ap < 15 nT). The model is based on Spherical Harmonic Analysis (SHA) of Global Ionospheric Maps GIM-TEC provided by JPL from 1996 to 2019. The SHA coefficients are calculated for low solar activity (SSN2 ≤ 20) and high solar activity (SSN2 ≥ 100) and linear interpolation is applied between them. The input parameters of the model are the geographic coordinates, time UT, day, month, year, and the sunspot number SSN2. The GTEC mapping accuracy is validated by comparing results of GTEC, IRI-2016 and IRI-Plas models with the independent median GIM-TEC observed by JPL and UPC for four seasons and local time of moderate solar activity (2012). The results testify that GTEC shows Root Mean Square Error, RMSE, about 2 times less than that of IRI-2016 and IRI-Plas TEC predictions. Model GTEC can be used alone for GIM-TEC prediction under quiet conditions. It is also incorporated as an option to IRI-Plas code to improve accuracy of TEC predictions with IRI-Plas model.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Global mapping of total electron content from GNSS observations for updating IRI-Plas model


    Beteiligte:
    Shubin, V.N. (Autor:in) / Gulyaeva, T.L. (Autor:in)

    Erschienen in:

    Advances in Space Research ; 69 , 1 ; 168-175


    Erscheinungsdatum :

    2021-09-25


    Format / Umfang :

    8 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch






    Comparing GNSS TEC data from the African continent with IRI-2016, IRI-Plas, and NeQuick predictions

    Liu, Jialong / Jia, Xiaolin / Zhu, Yongxing et al. | Elsevier | 2022



    Rover 3500 Vanden Plas AR-Test

    Br.Leyland,Rover,GB | Kraftfahrwesen | 1982