Generation of proxy GIM-TEC for extreme storms before the Era of GNSS observations

Otros/as autores/as

Universitat Politècnica de Catalunya. Departament de Matemàtiques

Universitat Politècnica de Catalunya. IonSAT - Grup de determinació Ionosfèrica i navegació per SAtèl·lit i sistemes Terrestres

Fecha de publicación

2022-01

Resumen

For the first time, we reconstructed global distribution of both the total electron content disturbance W index and TEC values for eight extreme storms (Dst < -250 nT) occurred before the epoch of GNSS observations in solar cycle 22. We created a model based on superposed epoch analysis of the training set of GIM-W maps of nine SC23 extreme storms. Global GIM-W index maps are calculated from 15-min UPC GIM-TEC (UQRG) as the logarithmic deviation of instantaneous TEC from the monthly median GIMMTEC empirical model. We introduced the storm phase metrics for main and recovery phases of the positive ionosphere disturbance (the WU-index), the negative disturbance (the WL-index) and the ring current (the Dst-index). The probabilistic forecasting model (Pmodel) for SC22 GIM-Wx maps is developed based on GIM-W maps of the SC23 training set. The storm phase distribution Fx for the eight SC22 extreme storms is calculated from the proxy time shift (lag) of peak WUmax and WLmin relative to Dstmin. Proxy GIM-TECx maps are calculated by adjusting the GIM-MTEC median to the GIM-Wx prediction. Validation of the technique based on data of UPC and JPL for four intense ionospheric storms showed a root-mean-square error less than 3 TECU. The proposed technique can be applied for both the past and future forecasting of GIM-W index and GIM-TEC maps.


Peer Reviewed


Postprint (published version)

Tipo de documento

Article

Lengua

Inglés

Publicado por

John Wiley & sons

Documentos relacionados

https://agupubs.onlinelibrary.wiley.com/doi/epdf/10.1029/2021JA029846

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Derechos

https://creativecommons.org/licenses/by-nc-nd/4.0/deed.es

Open Access

Atribución-NoComercial-SinDerivadas 4.0 Internacional

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E-prints [72986]