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Evaluation of International Reference Ionosphere 2000 at a midlatitude station
Author(s) -
Mansilla G. A.
Publication year - 2007
Publication title -
radio science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.371
H-Index - 84
eISSN - 1944-799X
pISSN - 0048-6604
DOI - 10.1029/2006rs003536
Subject(s) - ionosonde , geomagnetic storm , international reference ionosphere , storm , ionosphere , middle latitudes , meteorology , atmospheric sciences , geomagnetic latitude , environmental science , earth's magnetic field , climatology , geology , total electron content , physics , geophysics , tec , electron density , quantum mechanics , magnetic field , electron
To check the validity of the latest version of the International Reference Ionosphere (IRI‐2000), which contains geomagnetic activity dependence based on an empirical storm time ionospheric correction (STORM model), comparison of measured f o F 2 values with those obtained from the model was made. To quantify the degree of accuracy of the IRI‐2000 model during disturbed conditions, the relative difference between the model outputs (with STORM model turned on and turned off options) and experimental data was calculated. The ionosonde f o F 2 data used were obtained at Ebro Observatory (40.8°N, 0.49°E; geomagnetic latitude 43.2°N) during intense geomagnetic storms occurring in the years 2000 and 2001 (high solar activity). Although only a few case study comparisons have been made, the results show that during storm conditions, predicted values with the STORM model included in IRI‐2000 follow the variations of f o F 2 data better than IRI‐2000 without the STORM model. In general, IRI‐2000 with the STORM model has almost 30–40% improvement over IRI‐2000 without the STORM model. The greater deviations between model outputs and observations are observed during the end of the main phase and early stage of the recovery phase. For this station, in general, IRI predictions with the STORM model underestimate f o F 2 data in February–March and significantly overestimate them in April–May.