Abstract

AbstractGeomagnetic storms can have a great impact on the Earth's upper atmosphere, that is, the ionosphere. The activity of the ionosphere could be more pronounced during geomagnetic storms, which can make key ionospheric parameters, like total electron content (TEC), very hard to be modeled. The use of a Global Navigation Satellite System (GNSS) navigation ionospheric model is a conventional option for users to correct the ionospheric delay, which could suffer from the effects of storms. In this study, the performance of Beidou Navigation Satellite System (BDS) navigation ionospheric model in the China region during the main phase of different classes of geomagnetic storms is investigated for the first time. The analysis of the results revealed that the accuracy of the BDS navigation ionospheric model was impacted to different degrees during the storms. The effects during strong storms were the greatest, followed by moderate and weak storms. The impact on the accuracy of the model was characterized by latitude and local time. Furthermore, the accuracy of the model during the same class of storms was not always at the same level. The finding in this study could benefit the prediction of GNSS navigation ionospheric models' performance during geomagnetic storms.

Highlights

  • Geomagnetic storms are magnetospheric disturbances which are characterized by increased particle fluxes in the ring current

  • Geomagnetic storms are primarily motivated by intense, long duration and southward interplanetary magnetic fields (IMFs)

  • In order to evaluate the performance of the Bei22 dou Navigation Satellite System (BDS) navigation ionospheric model during the main phase of different classes of storms, the real–measured slant total electron content (STEC) derived from

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Summary

Key Points:

The influence on the accuracy of the model during strong storms is greatest, followed by moderate and weak storms. The impact on the accuracy of the model is clearly characterized by the latitude and local time. The accuracy of the model is not comparable for the same class of storms. This article has been accepted for publication and undergone full peer review but has not been through the copyediting, typesetting, pagination and proofreading process, which may lead to differences between this version and the Version of Record. Please cite this article as doi: 56

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