Bibliography

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

Near Real-Time Global Plasma Irregularity Monitoring by FORMOSAT-7/COSMIC-2

This study presents initial results of the ionospheric scintillation in the F layer using the S4 index derived from the radio occultation experiment (RO-S4) on FORMOSAT-7/COSMIC-2 (F7/C2). With the sufficiently dense RO-S4 observations at low latitudes, it is possible to construct hourly, global scintillation maps to monitor equatorial plasma bubbles (EPBs). The preliminary F7/C2 RO-S4 during August 2019 to April 2020 show clear scintillation distributions around American and the Atlantic Ocean longitudes. The RO-S4 near Jicamarca are compared with range-time-intensity (RTI) maps of the 50 MHz radar, and the results show that the occurrence of intense RO-S4 in the range 0.125–0.5 are co-located with the bottomside of the spread-F patterns. Increases in RO-S4 at the upward phase of bottom-side oscillations is theoretically consistent with large-scale wave seeding of the EPBs. The locations and occurrences of the RO-S4 greater than 0.5 are consistent with airglows depletions from the NASA GOLD mission. Climatology analyses show that monthly occurrences of RO-S4 \textgreater 0.5 agree well with the monthly EPB occurrences in GOLD 135.6 nm image, and show a similar longitudinal distribution to that of DMSP and C/NOFS in-situ measurements. The results suggest that the RO-S4 intensities can be utilized to identify EPBs of specific scales.

Chen, Shih-Ping; Lin, Charles; Rajesh, Panthalingal; Liu, Jann-Yenq; Eastes, Richard; Chou, Min-Yang; Choi, Jong-Min;

Published by: Journal of Geophysical Research: Space Physics      Published on:

YEAR: 2021     DOI: 10.1029/2020JA028339

equatorial plasma bubbles; FORMOSAT-7/COSMIC-2; global observation of limb and disk; GNSS scintillation; radio occultation; S4 index