Granger causality analysis of deviation in total electron content during geomagnetic storms in the equatorial region

The total electron content (TEC) in the ionosphere widely influences Global Navigation Satellite Systems (GNSS) especially for critical applications by inducing localized positional errors in the GNSS measurements. These errors can be mitigated by measuring TEC from stations located around the world...

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Bibliographic Details
Published inJournal of engineering and applied science (Online) Vol. 68; no. 1; pp. 1 - 25
Main Authors Iyer, Sumitra, Mahajan, Alka
Format Journal Article
LanguageEnglish
Published Berlin/Heidelberg Springer Berlin Heidelberg 01.12.2021
Springer Nature B.V
SpringerOpen
Subjects
Auroral electrojets
Causality
Cointegration
Engineering
Equatorial regions
Errors
Forecasting
Geomagnetic storm
Geomagnetism
Global navigation satellite system
Global Positioning System
Global positioning systems
GPS
Granger causality
Ionosphere
Magnetic fields
Magnetic storms
Mathematical models
Modelling
Navigation satellites
Perturbation
Receivers & amplifiers
Solar cycle
Storms
Sun
Total Electron Content
Wind
Geomagnetic storm
Total electron content
Cointegration
Ionosphere
Granger causality
Global Positioning System
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Summary:The total electron content (TEC) in the ionosphere widely influences Global Navigation Satellite Systems (GNSS) especially for critical applications by inducing localized positional errors in the GNSS measurements. These errors can be mitigated by measuring TEC from stations located around the world at various temporal and spatial scales and using them for advanced forecasting of TEC. The TEC can be used as a tool in understanding space weather phenomena such as geomagnetic storms which cause disruptions in the ionosphere. This paper examines the causal relationship between perturbations in TEC caused by geomagnetic storms. The causality between two geomagnetic indices auroral electrojet (AE) and disturbed storm index (Dst) and TEC is investigated using Granger causality at two low-latitude stations, Bangalore and Hyderabad. The outcomes of this study strengthen the regional understanding and modeling of ionospheric parameters which can contribute towards the global efforts for modeling and reducing the ionospheric effects on trans-ionospheric communication and navigation. The causal inferences combined with the data-driven model can be useful in identifying the correct and informative physical quantities to improve the forecasting models.
ISSN:1110-1903
2536-9512
DOI:10.1186/s44147-021-00007-x