Application of generalized singular value decomposition to ionospheric tomography

Equatorial electrojet (EEJ) data, which are considered as a proxy index of equatorial electric field, are analyzed in conjunction with equatorial ionosonde, total electron content (TEC) and scintillation data near the equatorial ionization anomaly (EIA) crest for the equinoctial months of high solar activity years (2011–2012) to identify any precursor index of postsunset evolution of equatorial electron density irregularities and subsequent occurrence of scintillation near the northern EIA crest. Only geomagnetically quiet and normal electrojet days are considered. The diurnal profiles of EEJ on the scintillation days exhibit a secondary enhancement in the afternoon to presunset hours following diurnal peaks. A series of electrodynamical processes conducive for generation of irregularities emerge following secondary enhancement of EEJ. Latitudinal profile of TEC exhibits resurgence in EIA structure around the postsunset period. Diurnal TEC profile near the EIA crest resembles postsunset secondary enhancement on the days with afternoon enhancement in EEJ. Occurrence of equatorial spread F and postsunset scintillation near the EIA crest seems to follow the secondary enhancement events in EEJ. Both the magnitude and duration of enhanced EEJ are found to be important for postsunset intensification of EIA structure and subsequent occurrence of equatorial irregularities. A critical value combining the two may be considered an important precursor for postsunset occurrence of scintillation near the EIA crest. The results are validated using archived data for the years 1989–1990 and explained in terms of modulation effects of enhanced equatorial fountain.

Research on total electron content (TEC) empirical models is one of the important topics in the field of space weather services. Global TEC empirical models based on Global Ionospheric Maps (GIMs) TEC data released by the International GNSS Service (IGS) have developed rapidly in recent years. However, the accuracy of such global empirical models has a crucial restriction arising from the non-uniform accuracy of IGS TEC data in the global scope. Specifically, IGS TEC data accuracy is higher on land and lower over the ocean due to the lack of stations in the latter. Using uneven precision GIMs TEC data as a whole for model fitting is unreasonable. Aiming at the limitation of global ionospheric TEC modelling, this paper proposes a new global ionospheric TEC empirical model named the TECM-GRID model. The model consists of 5183 sections, corresponding to 5183 grid points (longitude 5°, latitude 2.5°) of GIM. Two kinds of single point empirical TEC models, SSM-T1 and SSM-T2, are used for TECM-GRID. According to the locations of grid points, the SSM-T2 model is selected as the sub-model in the Mid-Latitude Summer Night Anomaly (MSNA) region, and SSM-T1 is selected as the sub-model in other regions. The fitting ability of the TECM-GRID model for modelling data was tested in accordance with root mean square (RMS) and relative RMS values. Then, the TECM-GRID model was validated and compared with the NTCM-GL model and Center for Orbit Determination in Europe (CODE) GIMs at time points other than modelling time. Results show that TECM-GRID can effectively describe the Equatorial Ionization Anomaly (EIA) and the MSNA phenomena of the ionosphere, which puts it in good agreement with CODE GIMs and means that it has better prediction ability than the NTCM-GL model.

Characterization of GPS-TEC over African equatorial ionization anomaly (EIA) region during 2009–2016

We use multiple instruments data to investigate the behavior of the equatorial and low‐latitude ionosphere during the geomagnetically active and quiet period of November 1–6, 2021. In this context, total electron content (TEC) data obtained from the Global Positioning System (GPS) receivers in the equatorial and low‐latitude regions of Asia, Africa, and America are used to assess variations in plasma density during the storm. The storm‐time ionization levels were found to vary significantly in the crests of the Equatorial Ionization Anomaly (EIA) region over the 3 longitudes. The Rate of Change TEC Index (ROTI) derived from GPS receiver measurements, is used to study the equatorial/low‐latitude ionospheric plasma irregularities at various longitudes under geomagnetically quiet and disturbed conditions. Observations showed longitudinal variations in the ionospheric irregularities under both quiet and disturbed conditions. Some days exhibit a decrease in the strength of the midnight plasma irregularities toward the East, that is, the irregularities are more pronounced in West America, less common in East America, and almost non‐existent in Africa and Asia. Our investigations show this storm prevented the occurrence of plasma irregularities at the equatorial/low‐latitude region in the American sector during the night following the main phase. In general, no significant storm effects were observed at the target locations in Africa and Asia. The existence of westward Prompt Penetration Electric Field (PPEF) and the Equatorial Electrojet (EEJ) during the main phase, from midnight to noon, is clearly related with the constriction of plasma diffusion and the consequent suppression of plasma irregularities. Thus, the longitudinal dependence for the generation of midnight plasma irregularities during this storm is mainly influenced by local time occurrence of maximum ring current, and the ionospheric electric fields.

This study is a preliminary analysis of the accuracy of various ionosphere models to correct single frequency altimeter height measurements for ionospheric path delay. In particular, research focused on adjusting empirical and parameterized ionosphere models in the parameterized real-time ionospheric specification model (PRISM) 1.2 using total electron content (TEC) data from the Global Positioning System (GPS). The types of GPS data used to adjust PRISM included GPS line-of-sight (LOS) TEC data mapped to the vertical, and a grid of GPS derived TEC data in a Sun-fixed longitude frame. The adjusted PRISM TEC values, as well as predictions by IRI-90, a climatological model, were compared to TOPEX/Poseidon (T/P) TEC measurements from the dual-frequency altimeter for a number of TIP tracks. When adjusted with GPS LOS data, the PRISM empirical model predicted TEC over 24 1 h data sets for a given local time to within a global error of 8.60 TECU rms during a midnight centered ionosphere and 9.74 TECU rms during a noon centered ionosphere. Using GPS derived sun-fixed TEC data, the PRISM parameterized model predicted TEC within an error of 8.47 TECU rms centered at midnight and 12.83 TECU rms centered at noon. From these best results, it is clear that the proposed requirement of 3-4 TECU global rms for TOPEX/Poseidon Follow-On will be very difficult to meet, even with a substantial increase in the number of GPS ground stations, with any realizable combination of the aforementioned models or data assimilation schemes.

Intense geomagnetic storms offer opportunity to understand ionospheric response to space weather events. Using Total Electron Content (TEC) data from stations along the east African sector, the two most intense storms during the 24th solar cycle, with similarly occurrence season and time were studied. We observe that ionospheric effect during the main phase is not a function of the severity of the storm, whereas the more intense storm shows greater influence on the African ionosphere during the recovery phase. Plasma movement within the equatorial ionization anomaly (EIA) was evident particularly during the recovery phase, especially during the 2015 event. For both storms, the nighttime/early morning ionospheric effect is more pronounced than the daytime effects across all stations.
 

Analysis of the north–south asymmetry of the equatorial ionization anomaly around 110°E longitude

Abstract. In this paper the Total Electron Content (TEC) data of eight Global Positioning System (GPS) stations of the EUREF network (AUT1, Thessaloniki, TUC2, Crete in Greece, MATE, Matera, LAMP, Lampedusa in Italy, GAIA, in Portugal, RABT, Rabat, EVPA, Evpatoria in Ukrain and TRAB, Trabson in Turkey) were analysed using wavelet analysis in order to detect any frequency dependence of the correlation between TEC over different stations. In the same time frequency dependence of Dst (Global geomagnetic field disturbances) and TEC variations over each GPS station are searched in order to detect any correlation between them. The main conclusion of this analysis is that the components of TEC variation with periods <3 h are more suitable in searching for earthquake precursors. On the base of this conclusion the analyzed TEC series are searched for possible precursory phenomena on the occasion of the seismic activity of the last quarter of 2005 in the area of Greece. An exalting (i.e. an increase in the amplitude) of variations with periods up to the tidal ones (period of 6 h,8 h,12 h) may be observed a month before and during the seismic activity over the stations TUC2 and AUT1 and may be attributed to this tectonic activity. Statistical properties of the 1.5 h component of the Total Vertical Electron Content (TVEC) over the nearest GPS stations (TUC2 and AUT1) of the areas of the seismic activity indicate that this component present characteristic exalting in the time period of 15 days before the shock.

Ionospheric slab thickness at the equatorial anomaly region after the deep solar minimum of cycle 23/24

Studying the winter anomaly with altimeter-derived TEC data

Total electron content (TEC), which quantifies the quantity of free electrons in the Earth’s ionosphere, is a crucial parameter that experiences discrepancies during seismic events. This study investigates the potential of utilizing TEC prediction at the BAKO position in Indonesia during earthquakes. TEC data and solar parameters were collected for six preselected earthquakes, encompassing the earthquake event periods. Three prediction models, namely, ARMA, OKSM 1, and OKSM 2, were employed to predict TEC for a period spanning 8 days. The input parameters required for TEC prediction were obtained from the IONOLAB and OMNIWeb database. The OKSM 1 model is constructed with the input parameters like solar radio flux at 10.7 cm (F10.7), disturbance storm time index (Dst), solar wind (Sw), sunspot number (SSN), and TEC values, while the OKSM 2 model is developed with the parameters like geomagnetic indices (Kp and Ap) and solar indices SSN and F10.7 along with TEC data. The ARMA model is constructed with TEC data. The primary objective of this research is to assess the utility of TEC prediction based on the influence on input parameters for the kriging models and to identify the most effective model for predicting TEC variations associated with seismic events. Four evaluation metrics were systematically utilized to gauge the performance of each model. This rigorous evaluation aims to deliver perceptions into the predictive accuracy, reliability, and potential practical implications of TEC predicting during earthquakes. Upon comparison, the OKSM 2 model demonstrated superior predictive accuracy, exhibiting a notable agreement with the true TEC. The results suggest that OKSM 2 holds promise as a reliable model for earthquake‐related TEC prediction. The average RMSE values range from 4.06 to 8.06, indicating the models’ ability to predict seismic events with a reasonable magnitude of error. Similarly, the average MAE values, ranging from 3.32 to 6.71, underscore the models’ overall accuracy in predicting the absolute differences between actual and predicted TEC. The CC values, averaging between 0.97 and 0.99, highlight a strong relationship between predicted and actual TEC values. Additionally, the average sMAPE values, ranging from 0.11 to 0.21, demonstrate the models’ effectiveness in minimizing percentage‐based errors. While variations exist across different earthquakes, these average metrics collectively suggest promising predicting capabilities.

Modeling of GPS-TEC using QR-decomposition over the low latitude sector during disturbed geomagnetic conditions

Mapping of the Ionospheric Total Electron Content over the East African Low–Latitude Region

Total electron content (TEC) data, obtained from satellites, are used in the search for imprints for identifying the probability factor of an impending earthquake. Extraction of earthquake induced signature is done mainly from day-to-day variations in TEC peak (TECpeak.). The use of a single parameter such as TECpeak is not always enough to formulate such a pointer. The paper therefore focuses on the need to introduce other markers such as the shape of TEC profile and to utilize any modification in the profile shape caused by an impending earthquake to identify precursors. An automatic pattern matching approach for processing global positioning system (GPS) generated TEC records is introduced to achieve this aim and TEC profiles are passed through a template framed from the time series of quiet day data. The Dynamic Time Warping (DTW) algorithm is adopted to look for deviations in the entire TEC profile of days prior to the earthquake with respect to the template. Variation, if any, would be used as an index of earthquake induced signature. A few case studies using this algorithm are presented in the paper. Work is based on TEC data collected from the GPS receiver at Guwahati (26° 10′ N, 91° 45′ E), an equatorial anomaly crest station.

The ionospheric total electron content (TEC) data from 05 to 10 January 2013 (UT) were examined by two-dimensional principal component analysis (2DPCA) and revealed a TEC anomaly related to the volcanic eruption in Colima, Mexico on 06 January, 2013. A TEC anomaly was detected above the volcano from 21:00 to 21:05 on 06 January 2013 (UT). The anomaly occurred for at least 5 minutes, during this time period we could identify the equatorial ionization anomaly (EIA). The shock acoustic wave produced by eruption-induced seismic activity may be the cause of the observed TEC anomaly. We show that it is possible to monitor or predict volcanic eruptions and their associated seismic activity through the use of two-dimensional principal component analysis of the resulting TEC anomalies.