GPS Network Research Articles

Evil and allies: Opportunistic gulls as both spreaders and sentinels of antibiotic‐resistant bacteria in human‐transformed landscapes

Abstract Human‐transformed residuals, especially those derived from human waste (dumps), farmland, and livestock are involved in the emergence of antibiotic‐resistant bacteria (ARB) in the environment. Wildlife can act as vectors of ARB dispersal through different environments, but also as sentinels to detect the early spread and determine ARB sources. The development of integrated monitoring programmes focused on wildlife would help to anticipate the risks of ARB to humans and livestock. We used the yellow‐legged gull (Larus michahellis) as a model species to investigate and monitor the spatial patterns of ARB dispersal across an extensive farmland region located in northeastern Spain (Lleida). By integrating GPS tracking data and ARB clinical testing for 26 individuals within a network analysis framework, we modelled the risk of spatial pathogen spread through faeces during the bacteria‐transmission latency period (16 days after sample collection). Additionally, we created a connectivity network to determine the main sources of ARB in the area, focusing on three main habitats of special risk for infection: dumps, livestock facilities, and irrigation ponds. Seven individuals were infected by Escherichia coli, with one also co‐infected with Listeria monocytogenes and Salmonella spp. Potential pathogen dispersal distances ranged from 1.13 km to 23.13 km from the breeding colony. Our network analyses revealed 54 main nodes (i.e. high‐risk habitats recurrently visited by tracked gulls) and 1182 links among them. Our findings revealed a high degree of connectivity between the breeding area, located in a shallow lake, and nearby dumps, highlighting them as significant contributors to ARB dispersal. Synthesis and applications: The integration of GPS data, pathogen testing and network analyses can shed further light on pathogen dynamics by creating spatial risk maps and identifying ARB sources. In combination with complementary molecular epidemiology techniques within a One Health framework, our approach can emerge as an important tool for monitoring ARB dynamics within highly human‐transformed ecosystems. This may empower managers for the development of targeted ARB monitoring programmes and effective mitigation strategies, ultimately improving both animal and public health.

Deformation and displacements of Earth’s surface in Turkish earthquakes era in February 2023 by geodesy data

The work analyzes the connection between a series of Turkish earthquakes in February 2023 and coseismic displacements and deformations on the Earth's surface. In areas of seismic rupture during the five days, there are recordings of three earthquakes on February 6 with magnitudes 7.8, 6.7, 7.5 and then for 5 days period – 42 events of magnitude 4.5–6.0. This work analyzed data obtained by various geodesy methods in the epicentral region. Coseismic effects in a 300 kilometers zone, covering a significant part of the East Anatolian Fault, are considered. Relative displacements up to 6 m have been recorded, with an average value 4 m. When for studying far-field effects, we used GPS network data from 27 international stations, of which seven stations located in Turkey. For the closest to the epicenters of the main aftershock on February 6, 2023, MERS station received coseismic 3D displacements up to 20 mm. The displacement and deformation fields have been constructed according to IGS data. Rates of coseismic deformations in the far zone reach up 10–8 , which is an order of magnitude higher than the background values of 10–9 . Post-seismic horizontal and vertical displacements rates of the Earth's surface in areas of Turkey, located to the southwest of the earthquake epicenters can be associated with floods. A study of displacements rates and deformations of the territory was carried out Turkey and its surroundings in the era of 2017–2023. Highlighted decrease displacement rates two years before seismic activation in 2023. The resulting picture of displacement and deformation rates reflects a current processes in the territory located on the borders of Anatolian Block and tectonic plates: Eurasian, Arabian, and African.

Postseismic processes in the region of the july 29, 2021 Chignik earthquake, Alaska. Part II: temporal evolution of displacements and correlation with aftershock activity

Postseismic displacements in the source region of the July 29, 2021 Chignik M8.2 earthquake, Alaska, are analyzed based on the data from the GPS network sites. It is shown that these displacements have a nature of a postseismic creep (afterslip). The rate of postseismic displacements of the points on the Earth’s surface (GPS sites) decreases with time by the power law close to 1/t, where t is time after the earthquake. On the time interval of two years, the displacement magnitudes increase in time by the law of logarithmic creep. Using the regional catalog of the Alaska earthquakes, we have analyzed the aftershocks of the Chignik earthquake. The analysis has shown that the postseismic displacements at different GPS sites are proportional to the displacements in the seismotectonic flow of the rock mass caused by residual displacements in the aftershock sources. This allows the total displacements in the aftershock sources to be considered as produced by a single mechanism of postseismic creep deformation in the source region of the Chignik earthquake.

Ubiquitous computation in internet of vehicles for human-centric transport systems

The Internet of Vehicles (IoV) has the potential to bring about a revolutionary transformation in transportation through its influence on human behavior and interactions between users and vehicles. However, interoperability challenges between retailer organizations and manufacturers present a barrier to decision-making processes and impact the human-centric nature of the IoV. Ethical dilemmas arise as a result of the IoV’s inability to prevent accidents, particularly in critical situations. This study aims to enhance the IoV’s effectiveness by carefully selecting and improving essential attributes from various data sources, including sensors, GPS, 5G or 6G communication networks, and real-time data provisioning. To achieve the aim of the proposed study, a Multi-criterion Decision-making (MCDM) approach is proposed, which allows for the analysis and selection of optimal choices while taking into account various quantitative and qualitative factors. Despite the challenges posed by complex models and ambiguous data, MCDM remains an indispensable technique for aligning transportation systems with current expectations. The CRITIC and TOPSIS MCDM-enabled methodologies are employed to analyze IoV architecture, prioritizing significant elements that impact system performance and identifying optimal solutions by considering complications from worst-case scenarios. The study will assist engineers, scientists, and organizations to develop smart IoV systems that will cater to human needs by improving mobility and inspiration among users.

Space interferometer orbit determination with multi-GNSS

Spacecraft positioning plays a crucial role in scientific space mission design, as well as in the further scheduling of scientific observations for such a mission. We examine the application of global navigation satellite systems (GNSS) to solve the orbit determination problem in a pure space very long baseline interferometer (VLBI) project. A network of GPS, GLONASS, Galileo and BeiDou navigation satellites may be a more efficient solution to determining the position and velocity of space radio telescopes and space interferometer baselines. For such a project, it is necessary to take into account the special conditions of GNSS observations, as well as the high accuracy of determining not only position but also velocity. In this paper, we estimate visibility of navigation satellite systems for Low and Medium orbits of a pure space-VLBI system and simulate GNSS code and phase measurements. Orbit determination was performed on smoothed code measurements. Phase measurements simulated with a step of 1 s and combined in Doppler measurements yield average position and velocity errors of 1.01 m and 8.8 mm/s in Medium Earth orbit. The results showed that GNSS observations are sufficient to solve the problems of orbit determination of a space-VLBI interferometer both in Low-Earth and Medium Earth orbits.

Topographical Effects on Volcano Deformation Signal Intensity: Implications for GPS Network Configuration

AbstractVolcano GPS networks can capture vital information during volcanic unrest to aid with hazard assessment and eruption forecasting, but can be hindered by their discrete point locations and possibly miss key spatial information. We show how numerical models can reveal controls on spatial deformation signal intensity compared against GPS network design. Using the GPS network at Soufrière Hills Volcano (SHV), Montserrat, and a range of models, we explore expected surface deformation patterns. Peak horizontal deformation is located offshore, highlighting the difficulties with geodetic monitoring on small ocean‐island volcanoes. Onshore areas where the deformation signal is expected to be high are also identified. At SHV, topography plays a greater role in altering the relative distribution of surface displacement patterns than subsurface heterogeneity. Our method, which can be adapted for other volcanoes, highlights spatial areas that can be targeted for effective GPS station placement to help improve deformation monitoring efficiency.

CMONOC II Common Mode Error Analysis and Structural Region Division Research

The modern tectonic deformation of the Chinese mainland is dominated by landmass movements, and active tectonic block regions are geological units with a relatively uniform movement pattern. The removal of CMEs can provide more accurate GPS data for exploring the movement characteristics between active tectonic block regions. In order to improve the effect of CME extraction, we propose that the Crustal Movement Observation Network of China be divided into sub-regions based on the refined definition of active tectonic block regions of the Chinese mainland. In this paper, 247 stations in the CMONOC II network are used to form a large spatial scale GPS network and 6 sub-regions with small spatial scale GPS networks. For the large spatial scale GPS network, we compare and analyze the effects of PCA and ICA filtering, and the study shows that PCA is not suitable for CME extraction in this large spatial scale GPS network, while ICA filtering is better. Subsequently, the large spatial scale GPS network and six small spatial scale GPS networks were used to extract CME using ICA, with the results showing that the RMSE values of the residual time series of the large spatial scale GPS network were reduced by 9.60%, 17.08%, and 16.14% in the directions of E, N, and U, respectively, and that the subregions divided according to the refined and determined first-level active plots of the Chinese continent had their residual time series of the RMSE values were reduced by 26.19%, 26.95%, and 28.32% on average in the three respective directions of E, N, and U. The effect of extracting CMEs by dividing the subregions was 29.16%, 5.44%, and 39.84% higher than the effect of extracting them as a whole in the three directions of E, N, and U, respectively. The experimental results demonstrate that the CMONOC II observation network is an effective and feasible method to extract CMEs according to the finely defined active tectonic block region of the Chinese mainland at the first level.

Statistical analysis of regional STEC gradient trends for midlatitude ionosphere

In this study, the gradients of Total Electron Content (TEC) for a midlatitude region are estimated and grouped with respect to the distance between neighboring stations, time periods within a day, and satellite directions. Annual medians of these gradients for quiet days are computed as templates. The metric distances (L2N) and Symmetric Kullback-Leibler Distances (SKLD) are obtained between the templates and the daily gradient series. The grouped histograms are fitted to the prospective Probability Density Functions (PDF). The method is applied to the Slant Total Electron Content (STEC) estimates from the Turkish National Permanent GPS Network (TNPGN-Active) for 2015. The highest gradients are observed in the east-west axis with a maximum of 25 mm/km during a geomagnetic storm. The maximum differences from the gradient templates occur for neighboring stations within 100–130 km distance away from each other, during night hours, and for regions bordering the Black Sea and the Mediterranean in the northeast and southeast of Turkey. The empirical PDFs of the station-pair gradients are predominantly Weibull-distributed. The mean values of Weibull PDFs in all station groups are between 1.2 and 1.8 mm/km, with an increase during noon and afternoon hours. The standard deviations of the gradient PDFs generally increase during night hours. The algorithm will form a basis for quantifying the stochastic variations of the spatial rate of change of TEC trends in midlatitude regions, thus supplementing reliable and accurate regional monitoring of ionospheric variability.

LoRa localisation using single mobile gateway

Effective use of GPS and mobile networks for localisation in rangeland areas is constrained by their high power consumption and high deployment costs. Long-range (LoRa), a low-power wide area network (LPWAN) technology, can be employed to mitigate these challenges. In contrast to prior research where the prevalent approaches entail multiple gateways. This work proposes a valuable methodology focused on a single mobile LoRa gateway for localisation. A particle filtering and machine learning-based pipeline is employed to map the distance between a target node and the gateway from the received signal strength indicator (RSSI). Particle filtering is used to reduce the impact of noise on the RSSI values. Then, several machine learning techniques, such as support vector machines, random forest, and k-nearest neighbour, are used on the RSSI values to estimate the distance. The estimated distance is then used for tracking using a centroid pseudo-trilateration method. The proposed method was tested in a real-world semi-line-of-sight setting, using three datasets generated by LoRaWAN-specified hardware components and a server. Two forms of experiments were performed: active searching and passive monitoring. We propose an iterative estimation process to address the dilution of precision caused by the initial positions of the gateway required for active searching applications. The results show that active searching typically requires 2 to 3 hops to reach a target node. The accuracy of passive monitoring depends on the proximity of the gateway, which varies from 20 m to 170 m. This proposed approach has the potential to open the way for localising, tracking, or monitoring target objects within sparsely populated rangeland areas, even when resources are severely constrained.

Robust Imaging of Fault Slip Rates in the Walker Lane and Western Great Basin From GPS Data Using a Multi‐Block Model Approach

AbstractThe Walker Lane (WL) in the western Great Basin (GB) is an active plate boundary system accommodating 10%–20% of the relative tectonic motion between the Pacific and North American plates. Its neotectonic framework is structurally complex, having hundreds of faults with various strikes, rakes, and crustal blocks with vertical axis rotation. Faults slip rates are key parameters needed to quantify seismic hazard in such tectonically active plate boundaries but modeling them in complex areas like the WL and GB is challenging. We present a new modeling strategy for estimating fault slip rates in complex zones of active crustal deformation using data from GPS networks. The technique does not rely on prior estimates of slip rates from geologic studies, and only uses data on the surface trace location, dip, and rake. The iterative framework generates large numbers of block models algorithmically from the fault database to obtain many estimates of slip rates for each fault. This reduces bias from subjective choices about how discontinuous faults connect and interact to accommodate strain. Each model iteration differs slightly in block boundary configuration, but all models honor geodetic and fault data, regularization, and are kinematically self‐consistent. The approach provides several advantages over bespoke models, including insensitivity to outlier data, realistic uncertainties, explicit mapping of off‐fault deformation, and slip rates that are more objective and independent of geologic slip rates. Comparisons to the U.S. National Seismic Hazard Model indicate that ∼80% of our geodetic slip rates agree with their geologic slip rates to within uncertainties.

State geodetic network Kyrgyz Republic

This article describes the creation and development of GPS networks on the territory of the Kyrgyz Republic. The state geodetic GPS network consists of three levels: 0-order GPS network, 1st order GPS network and 2nd order GPS network. GPS points are combined with GGS points (State Geodetic Network). The adjusted coordinates of GPS points are obtained in the ITRF system for the epoch of 2005 (ITRF 2005).

Task offloading and trajectory control techniques in unmanned aerial vehicles with Internet of Things – An exhaustive review

Objectives: This article reviews and provides an exhaustive examination of task offloading and trajectory control techniques in unmanned aerial vehicles (UAVs) integrated with Internet of Things (IoT), highlighting their significance and impact on the UAV ecosystem. The paper begins by introducing the fundamental concepts of UAVs, IoT, and their integration, emphasizing the potential benefits and challenges of this union. Subsequently, it delves into an extensive exploration of task offloading, a critical aspect that optimizes UAV operations by distributing tasks between the UAV and edge/cloud computing resources. Various task offloading strategies, including computation offloading, data offloading, and control offloading, is discussed in detail, elucidating their role in optimizing resource utilization, energy efficiency, and real-time decision-making in UAVs.Methods: The review comprehensively covers trajectory control techniques, which are essential for ensuring UAVs can navigate through dynamic environments safely and efficiently. This study outlines the use of IoT technologies, such as GPS, sensors, and communication networks, to enable precise trajectory planning, obstacle avoidance, and adaptive path adjustments. It also discusses the integration of machine learning and AI algorithms for autonomous UAV navigation, taking into account environmental factors, mission objectives, and real-time data from IoT sources. The paper further discusses the challenges and potential security concerns associated with IoT integration in UAVs, as well as the emerging trends and future prospects of this dynamic field. It emphasizes the need for standardized protocols and robust cybersecurity measures to ensure the reliability and safety of UAV-IoT systems.Findings: This exhaustive review offers a comprehensive understanding of the synergistic relationship between UAVs and IoT, shedding light on the task offloading and trajectory control techniques that empower these autonomous aerial vehicles. By leveraging IoT technologies, UAVs are poised to continue transforming industries and driving innovation in ways previously unimaginable, making this interdisciplinary field an area of great promise and significance.

Slip Partitioning Across Subparallel Strands of the North Anatolian Fault in the Marmara Region

Summary Marmara Region hosts a substantial part of the inhabitants in Turkey, more than 30% of the total population in the cities of Istanbul, Bursa, and Kocaeli. This region has experienced several large earthquakes in the past and is still under threat of destructive earthquakes in the future. There, subparallel strands of the North Anatolian Fault (NAF) expand into the region, distributing the earthquake hazards across the whole region. Thus, it is a key issue to investigate how the tectonic process is distributed between these subparallel strands to discriminate their individual earthquake hazards. In this context, we used GPS slip rates to quantify the slip partitioning of the subparallel strands of the fault system. In addition to available slip rates compiled by Bulut et al. (2019) and Kreemer et al. (2014), we analyzed 71 GPS sites (51 continuous and 20 campaign-based) to intensify the GPS network in the region. GPS observations reveal 81.7%, 7.7%, and 10.7% slip ratios for northern, middle, and southern strands. Time series analysis for four continuous GPS stations in the western Marmara Region also confirms these ratios.

Singular Points of the Tremor of the Earth’s Surface

A method for studying properties of the Earth’s surface tremor, measured by means of GPS, is proposed. The following tremor characteristics are considered: the entropy of wavelet coefficients, the Donoho–Johnston wavelet index, and two estimates of the spectral slope. The anomalous areas of tremor are determined by estimating the probability densities of extreme values of the studied properties. The criteria for abnormal tremor behavior are based on the proximity to, or the difference between, tremor properties and white noise. The greatest deviation from the properties of white noise is characterized by entropy minima and spectral slope and DJ index maxima. This behavior of the tremor is called “active”. The “passive” tremor behavior is characterized by the maximum proximity to the properties of white noise. The principal components approach provides weighted averaged density maps of these two variants of extreme distributions of parameters in a moving time window of 3 years. Singular points are the points of maximum average densities. The method is applied to the analysis of daily time series from a GPS network in California during the period 2009–2022. Singular points of tremor form well-defined clusters were found. The passive tremor could be caused by the activation of movement in fragments of the San Andreas fault.

Vertical accuracy evaluation free access digital elevation models (DEMs): case Fergana Valley in Uzbekistan

In this study, the vertical accuracy of the Shuttle Radar Topography Mission Digital Elevation Model Version 2.0 (SRTM30), the Advanced Spaceborne Thermal Emission and Reflection Radiometer Global DEM Version 2.0 (ASTER GDEM2), and Advanced Land Observing Satellite World 3D Digital Surface Model Version 2.1 (ALOS AW3D30) was statistically assessed using GPS data. The Fergana Valley area was chosen as a study region, where the land surface can reflect tectonic processes. The values of ellipsoidal heights of 27 points of the regional GPS network were chosen as reference data. The geometric approach using GPS/leveling data and EGM96 global geopotential model-based geoid undulations was applied for geoid surface fitting. The geoid height corrections range ranged from –0.66 m to 0.87 m. Root-Mean-Square errors of ~10.0 m, ~16.4 m, and ~6.6 m was obtained for SRTM30, ASTER GDEM2, and ALOS AW3D30, respectively. It was found that compared with the reference model, all the global DEMs in mountainous areas generally overestimated elevation and the value of vertical accuracy at a 90% confidence level by 3-6 meters exceeded the declared by distributors. But ALOS AW3D30 proved to be the most accurate DEM that best represents the topography of the earth’s surface and could be used for some engineering applications in Fergana Valley.

Exploring the role of PPP–RTK network configuration: a balance of server budget and user performance

With atmospheric corrections generated from the server, precise point positioning real-time kinematic (PPP–RTK) can achieve high-precision solutions in a fast convergence. PPP–RTK users are concerned about how to use the corrections and the level of performance that can be achieved; thus, our research has focused on correction methods, a priori stochastic modeling, and positioning performance evaluation. Conversely, it is crucial for the server to improve the precision of corrections provided and to consider the balance between cost, computation burden and user performance, especially for commercial applications. We use different scales of the national GPS network of France to generate ionospheric and tropospheric corrections, and corresponding uncertainty information is generated by establishing error functions with respect to an inter-station distance. The quality of corrections and corresponding user performance are analyzed with inter-station distances varying from 22 to 251 km. The results show that the precision of atmospheric corrections can be improved with an increasing number of stations in the network, but the improvement is not significant when the inter-station distances are smaller than 50 km. Regarding user performance, compared to conventional PPP solutions with ambiguity resolution, the convergence time can be reduced by a maximum of 93% and 85% in the horizontal and vertical components, respectively, when the inter-station distance is about 23 km. However, a station spacing within 100 km can still support a 3-min convergence; thus, a balance of server budget and user performance should be considered instead of a dense network.

Unraveling contributions of Greenland's seasonal and transient crustal deformation during the past two decades

Contemporary research on Greenland surface mass balance (SMB) is largely focused on the characteristics of decadal or longer trends, periodic oscillations, and acceleration. However, the specific components of the SMB such as snowfall (SF), rainfall (RF) and runoff (RU), and their corresponding temporal and spatial variability remain poorly understood. Here, we explore the respective contributions of SF, RF, and RU to the seasonal and transient crustal deformations of Greenland during the past two decades using GPS network and satellite gravimetry (GRACE) datasets, and regional climate model output. Our study unraveled that the largest annual vertical displacement caused by precipitations is in southeastern Greenland, reaching 7.27 mm. The largest surface displacement caused by RU is in western Greenland, reaching 19.82 mm. Ice mass gain/loss in Greenland shows a clear correlation between latitude and temperature, with greater variations in the south compared to the north. The transient deformation signals in Greenland mainly manifested in terms of abrupt subsidence in 2010, followed by uplift in 2014. The 2014 uplift can mainly be attributable to the combined effect of SF, RF, and RU. The largest transient signal occurs in the southeast subregions, with peak-to-peak amplitude exceeding 10 mm. Transient crustal deformation is mainly caused by precipitation in southeastern Greenland, while the contribution of RU dominates most of the time and in most subregions. We find that even though RF is increasing due to an increasingly warmer climate, its effect on SMB is still negligible, when compared with SF and RU. In some subregions and some periods, SF could become the primary contributor to transient SMB variations in Greenland.

Present-day strain accumulations and fault kinematics at the Hatay Triple Junction using new geodetic constraints

The East Anatolian Fault (EAF), Cyprus Arc and Dead Sea Fault (DSF) intersect at the Hatay Triple Junction (HTJ) in southern Turkey, which is a tectonically controversial zone among researchers. Although it is not as active as the North Anatolian Fault (NAF) or other segments on the EAF in terms of seismicity, the HTJ accumulates strain causing considerable seismic activity in the region. Prior to this study, the strain accumulations and kinematics of the HTJ have not been precisely investigated using such a dense GPS network comprising permanent GPS stations, Turkish National Fundamental GPS Network (TUTGA) and campaign sites. Here, the fault slip rates and locking depths were constrained in the vicinity of HTJ using a new velocity field and improved block modeling. As per the results of block modeling, the EAF and Karatas-Osmaniye Fault (KOF) are fully locked down to depths of 15 km and 7 km, respectively. Furthermore, the Karasu Fault (KF) has a fully locked seismogenic zone to 7 km depth with a similar slip distribution to the EAF. Our kinematic model suggests 9.2 mm/yr left-lateral strike-slip rate and 2.0–2.7 mm/yr thrust faulting slip rate at the southwest end of the EAF. The KF appears to have left-lateral strike-slip at the rates ranging 4.0–5.5 mm/yr, while contrarily it has no significant normal/reverse faulting component. In addition, the KOF accommodates left-lateral strike-slip of 3.3–4.5 mm/yr and extension with the rates of 1.8–2.7 mm/yr. The new constraints on the fault slip rates associated with the HTJ correspond to predictions for a probable large earthquake with possible magnitude ranging from 7.2 to 7.6 for the EAF segment and 6.7–7.2 for the KF and KOF segments.

Inferences on the 2021 Ongoing Volcanic Unrest at Vulcano Island (Italy) through a Comprehensive Multidisciplinary Surveillance Network

In September 2021, the La Fossa crater at Vulcano, in Italy, entered a new phase of unrest. We discuss a set of monitoring parameters included in the INGV surveillance network, which closely tracked the sequence of effects related to the crisis. The low-frequency local seismicity sharply increased, while the GPS and tiltmeter networks recorded the inflation of the cone, as an effect of fluid expansion in the hydrothermal system. Gravity variations were probably the effects of fast processes within shallow sources. The anomalies in soil CO2 flux, fumarole temperature, and in plume SO2 flux marked the strong increase in the vapor output from crater fumaroles. The signs of the impending crisis had been evident in the chemical and isotopic composition of fumarole gases since July 2021. These geochemical anomalies were clearly indicative of the enhanced input of gases from a magmatic source. In October, the massive degassing also influenced the areas at the base of the cone. In some areas, soil CO2 degassing and the thermal aquifer recorded strong anomalies. By early November, the crisis reached its acme. Afterward, the monitored parameters started a slow and discontinuous decreasing trend although remaining, some of them, sensibly above the background for several months. The multidisciplinary approach proved decisive for the interpretation of the underlying processes acting in the different phases of the unrest, thus allowing a consistent evaluation of the multiple hazards.

Observation of Scintillation Enhancements and Large‐Scale Structures Within the Equatorial Ionization Anomaly During a Sudden Stratospheric Warming Event

AbstractTotal electron content (TEC) and L‐band scintillations measured by several networks of GPS and GNSS receivers that operate in South and Central America and the Caribbean region are used to observe the morphology of the equatorial ionization anomaly (EIA), examine the evolution of plasma bubbles, and investigate the enhancement of L‐band scintillations that occurred on February 12 and 13, 2016. A few weak and short magnetic storms developed these days, and a minor sudden stratospheric warming (SSW) event was initiated a few days before. During these unusual conditions, TEC maps reported a split of the otherwise continuous crests of the EIA and the formation of a large‐scale (thousands of kilometers) almost‐circular structure. The western part of the southern crest faded, and a north‐south aligned segment developed near the center of the South American continent, joining the north and south crests of the EIA, forming an anomaly that resembled a closed loop on the eastern side of the continent. Concurrently with the anomaly events, several GPS stations reported increases in the L‐band scintillation index from 0.4 to values greater than 1. We analyzed TEC values from receivers between ±6° from the magnetic equator to identify and follow TEC depletions associated with plasma bubbles when they reach different stations. Although the magnetic activity was moderate (Kp = 3°), we believe that the anomaly redistribution and the scintillation enhancements are not related to a prompt penetration electric field but to enhancing the semidiurnal lunar tide propitiated by the onset of the minor SSW event. We found that depending on the lunar tide phase cycle, the neutral wind's meridional component can augment sub‐km scale irregularities and enhance L‐band scintillations through the wind gradient instability when U·n < 0 or the action of wind gradients (U) within the bubbles. Our observations imply that the SSW event enables prominent changes in the thermosphere wind system at F‐region altitudes.