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  1. Abstract The occurrence of plasma irregularities and ionospheric scintillation over the Caribbean region have been reported in previous studies, but a better understanding of the source and conditions leading to these events is still needed. In December 2021, three ground-based ionospheric scintillation and Total Electron Content monitors were installed at different locations over Puerto Rico to better understand the occurrence of ionospheric irregularities in the region and to quantify their impact on transionospheric signals. Here, the findings for an event that occurred on March 13–14, 2022 are reported. The measurements made by the ground-based instrumentation indicated that ionospheric irregularities and scintillation originated at low latitudes and propagated, subsequently, to mid-latitudes. Imaging of the ionospheric F-region over a wide range of latitudes provided by the GOLD mission confirmed, unequivocally, that the observed irregularities and the scintillation were indeed caused by extreme equatorial plasma bubbles, that is, bubbles that reach abnormally high apex heights. The joint ground- and space-based observations show that plasma bubbles reached apex heights exceeding 2600 km and magnetic dip latitudes beyond 28 ° . In addition to the identification of extreme plasma bubbles as the source of the ionospheric perturbations over low-to-mid latitudes, GOLD observations also provided experimental evidence of the background ionospheric conditions leading to the abnormally high rise of the plasma bubbles and to severe L-band scintillation. These conditions are in good agreement with the theoretical hypothesis previously proposed. Graphical Abstract 
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    Free, publicly-accessible full text available December 1, 2024
  2. The low-latitude ionosphere has an active behavior causing the total electron content (TEC) to vary spatially and temporally very dynamically. The solar activity and the geomagnetic field have a strong influence over the spatiotemporal distribution of TEC. These facts make it a challenge to attempt modeling the ionization response. Single frequency GNSS users are particularly vulnerable due to these ionospheric variations that cause degradation of positioning performance. Motivated by recent applications of machine learning, temporal series of TEC available in map formats were employed to build an independent TEC estimator model for low-latitude environments. A TEC dataset was applied along with geophysical indices of solar flux and magnetic activity to train a feedforward artificial neural network based on a multilayer perceptron (MLP) approach. The forecast for the next 24 h was made relying on TEC maps over the Brazilian region using data collected on the previous 5 days. The performance of this approach was evaluated and compared with real data. The accuracy of the model was evaluated taking into account seasonality, spatial coverage and dependence on solar flux and geomagnetic activity indices. The results of the analysis show that the developed model has a superior capacity describing the TEC behavior across Brazil, when compared to global ionosphere maps and the NeQuick G model. TEC predictions were applied in single point positioning. The achieved errors were 27% and 33% lower when compared to the results obtained using the NeQuick G and global ionosphere maps, respectively, showing success in estimating TEC with small recent datasets using MLP. 
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  3. null (Ed.)