Bibliography

Signatures of Equatorial Plasma Bubbles and Ionospheric Scintillations from Magnetometer and GNSS Observations in the Indian Longitudes during the Space Weather Events of Early September 2017

Scintillation due to ionospheric plasma irregularities remains a challenging task for the space science community as it can severely threaten the dynamic systems relying on space-based navigation services. In the present paper, we probe the ionospheric current and plasma irregularity characteristics from a latitudinal arrangement of magnetometers and Global Navigation Satellite System (GNSS) stations from the equator to the far low latitude location over the Indian longitudes, during the severe space weather events of 6–10 September 2017 that are associated with the strongest and consecutive solar flares in the 24th solar cycle. The night-time influence of partial ring current signatures in ASYH and the daytime influence of the disturbances in the ionospheric E region electric currents (Diono) are highlighted during the event. The total electron content (TEC) from the latitudinal GNSS observables indicate a perturbed equatorial ionization anomaly (EIA) condition on 7 September, due to a sequence of M-class solar flares and associated prompt penetration electric fields (PPEFs), whereas the suppressed EIA on 8 September with an inverted equatorial electrojet (EEJ) suggests the driving disturbance dynamo electric current (Ddyn) corresponding to disturbance dynamo electric fields (DDEFs) penetration in the E region and additional contributions from the plausible storm-time compositional changes (O/N2) in the F-region. The concurrent analysis of the Diono and EEJ strengths help in identifying the pre-reversal effect (PRE) condition to seed the development of equatorial plasma bubbles (EPBs) during the local evening sector on the storm day. The severity of ionospheric irregularities at different latitudes is revealed from the occurrence rate of the rate of change of TEC index (ROTI) variations. Further, the investigations of the hourly maximum absolute error (MAE) and root mean square error (RMSE) of ROTI from the reference quiet days’ levels and the timestamps of ROTI peak magnitudes substantiate the severity, latitudinal time lag in the peak of irregularity, and poleward expansion of EPBs and associated scintillations. The key findings from this study strengthen the understanding of evolution and the drifting characteristics of plasma irregularities over the Indian low latitudes.

Vankadara, Ram; Panda, Sampad; Amory-Mazaudier, Christine; Fleury, Rolland; Devanaboyina, Venkata; Pant, Tarun; Jamjareegulgarn, Punyawi; Haq, Mohd; Okoh, Daniel; Seemala, Gopi;

Published by: Remote Sensing      Published on: jan

YEAR: 2022     DOI: 10.3390/rs14030652

space weather; equatorial plasma bubbles; ionospheric irregularity; global navigation satellite system; magnetometer; poleward drift; rate of change of TEC index; scintillations; storm-time electric currents

Creating a Database to Identify High-Latitude Scintillation Signatures With Unsupervised Machine Learning

In high latitudes, Global Navigation Satellite System (GNSS) signals experience scintillation due to moving irregularity structures in the ionosphere. These develop as a result of different physical mechanisms, which are as yet principally described on an elementary level for certain storm cases and events. Since there are years of GNSS data available from stations around the globe, we are investigating an unsupervised Machine Learning approach to extract a large variety of groups of scintillation events with similar features. We create a database containing high-rate scintillation events from two geomagnetic storm cases and several stations in the high-latitude region of the Northern hemisphere. By clustering high-rate signatures in signal phase and power according to their major signal characteristics with an agglomerative hierarchical clustering, it is possible to extract different groups of similar types of scintillation signatures. As a result of this study, the database of scintillation signatures in various locations in the auroral oval and polar cap evolves and will be further expanded beyond the storm cases studied in this paper. These can then be linked to the geomagnetic conditions and dynamics in the ionosphere through additional datasets from other instruments, therefore potentially helping us to get a further insight into the ionospheric irregularity physics.

Bals, Anna-Marie; Thakrar, Chintan; Deshpande, Kshitija;

Published by: IEEE Journal of Radio Frequency Identification      Published on:

YEAR: 2022     DOI: 10.1109/JRFID.2022.3163913

Databases; Feature extraction; Fluctuations; global navigation satellite system; GNSS data noise elimination; GNSS scintillation; Indexes; Instruments; ionospheric scintillation event detection; Radiofrequency identification; unsupervised machine learning

Assessment of the predictive capabilities of NIGTEC model over Nigeria during geomagnetic storms

The Nigerian Total Electron Content (NIGTEC) is a regional neural network-based model developed by the Nigerian Centre for Atmospheric Research to predict the Total Electron Content (TEC) at any location over Nigeria. The addition of the disturbance storm time (Dst) index as one of NIGTEC s input layer neurons raises a question of its accuracy during geomagnetic storms. In this paper, the capability of NIGTEC in predicting the variability of TEC during geomagnetic storms has been assessed. TEC data predicted by NIGTEC is compared with those derived from Global Navigation Satellite System (GNSS) over Lagos (6.5oN, 3.4oE) and Toro (10.1oN, 9.12oE) during the intense storms in March 2012 and 2013. The model s predictive capability is evaluated in terms of Root Mean Square Error (RMSE). NIGTEC reproduced a fairly good storm time morphology in VTEC driven by the prompt penetration electric field and the increase in thermospheric O/N2. Nevertheless, it failed to predict the increase in TEC after the intense sudden impulse of 60 nT on 8 March 2012. And it could not capture the changes in VTEC driven by the storm time equatorward neutral wind especially during 18:00–24:00 UT. Consequently, the RMSEs were higher during this time window, and the highest RMSE value was obtained during the most intense storm in March 2012.

Amaechi, Paul; Humphrey, Ibifubara; Adewoyin, David;

Published by: Geodesy and Geodynamics      Published on: nov

YEAR: 2021     DOI: 10.1016/j.geog.2021.09.003

geomagnetic storm; global navigation satellite system; Nigerian Total Electron Content (NIGTEC); total electron content

Effects of the 12 May 2021 Geomagnetic Storm on Georeferencing Precision

In this work, we present the positioning error analysis of the 12 May 2021 moderate geomagnetic storm. The storm happened during spring in the northern hemisphere (fall in the south). We selected 868 GNSS stations around the globe to study the ionospheric and the apparent position variations. We compared the day of the storm with the three previous days. The analysis shows the global impact of the storm. In the quiet days, 93\% of the stations had 3D errors less than 10 cm, while during the storm, only 41\% kept this level of accuracy. The higher impact was over the Up component. Although the stations have algorithms to correct ionospheric disturbances, the inaccuracies lasted for nine hours. The most severe effects on the positioning errors were noticed in the South American sector. More than 60\% of the perturbed stations were located in this region. We also studied the effects produced by two other similar geomagnetic storms that occurred on 27 March 2017 and on 5 August 2019. The comparison of the storms shows that the effects on position inaccuracies are not directly deductible neither from the characteristics of geomagnetic storms nor from enhancement and/or variations of the ionospheric plasma.

Valdés-Abreu, Juan; Díaz, Marcos; Báez, Juan; Stable-Sánchez, Yohadne;

Published by: Remote Sensing      Published on: jan

YEAR: 2021     DOI: 10.3390/rs14010038

Geomagnetic storms; total electron content; global navigation satellite system; Global positioning system; precise point positioning; rate of change of the tec index