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Recent advances in distribution and miniaturization among spacecraft and expansion of global navigation satellite systems (GNSS) motivate the Distributed Multi‐GNSS Timing and Localization system. The DiGiTaL system is intended to provide nanosatellite swarms with unprecedented centimeter‐level relative navigation accuracy in real time and nanosecond‐level time synchronization through the integration of a multiconstellation GNSS receiver, a chip‐scale atomic clock, and an intersatellite link. This paper describes DiGiTaL's hardware and software design, architecture, and navigation software in detail. The swarming spacecraft are grouped into subsets, where differential GNSS is performed by a precise orbit determination module with integer ambiguity resolution in real time. The resulting precise orbits are then exchanged and fused by a swarm determination module, creating full‐swarm knowledge. Finally, the DiGiTaL architecture is integrated into CubeSat avionics and tested with key hardware in the loop using Stanford's GNSS navigation testbed. For the first time, this paper shows the capability to perform centimeter‐level precise relative navigation using commercial‐off‐the‐shelf CubeSat hardware for spacecraft swarms. [ABSTRACT FROM AUTHOR]

Thanks to advances in technology such as Internet-based mapping and the development of special inks, papers and global positioning systems, map making for vision impaired people can provide a range of products (e.g., tactile, haptic and audio-tactile maps) that can improve their independence, self-confidence and everyday life. The applications of tactile maps include learning spatial concepts and geography; audio-tactile maps combined with access to geospatial information can enhance mobility and independence. In 1998, the Mapping Services Branch (MSB) of the Earth Sciences Sector of Natural Resources Canada initiated a tactile mapping program. Now referred to as the Government on Line—Mapping for the Visually Impaired Project (Natural Resources Canada 2003a), it aims to serve the community with special needs, with emphasis on those who are blind or visually impaired, their teachers and mobility instructors. This technical paper discusses the various types of tactile and audio-tactile maps of Canada developed by the MSB in cooperation with its partners and describe the current research and development activities carried out within the project. It also leads the reader to further information on audio-tactile maps and touch- and sound-based computer interfaces. [ABSTRACT FROM AUTHOR]

The high‐precision prediction of total ionospheric electron content (TEC) is of great significance for improving the accuracy of global navigation satellite systems. There are two problems with the current prediction of TEC: (a) The existing TEC prediction models mainly based on stacked structure, which has insufficient predictive ability when the network has fewer layers, and loss of fine‐grained features when there are more layers, resulting in a decrease in predictive performance; (b) The existing research on ionospheric TEC prediction mainly focuses on building deep learning prediction models, while there is little research on optimizing the hyper‐parameters of TEC prediction models. Optimization can help find a better quasi‐optimal hyperparameter combination and improve the performance of the model. This paper proposed an automatic deep learning framework for global TEC map prediction, named MAOOA‐Residual‐Attitude‐BiConvLSTM. This framework includes a TEC prediction model, Residual‐Attention‐BiConvLSTM, which can simultaneously consider both coarse‐grained and fine‐grained spatiotemporal features. It also includes an optimization algorithm, MAOOA, for optimizing the hyper‐parameters of the model. We conducted comparative experiments between our framework and C1PG, ConvLSTM, ConvGRU, and ED‐ConvLSTM during high solar activity years, low solar activity years, and a magnetic storm event. The results indicate that in all cases, the framework proposed in this paper outperforms the comparative models. Plain Language Summary: There are two main problems I n the existing TEC prediction field: (a) The prediction model mainly adopts a sequential stacking structure, losing fine‐grained spatiotemporal features, which leads to insufficient prediction ability of the model. (b) Current research mainly focuses on TEC prediction models, with little attention paid to hyper‐parameter optimization of prediction models. Model optimization can find hyperparameter combinations that make the model's performance close to the optimal solution. This paper proposed a TEC prediction and optimization framework, MAOOA‐Residual‐Attitude‐BiConvLSTM, in which Residual‐Attitude‐BiConvLSTM is used for TEC map prediction. By incorporating skip layer design, this model can simultaneously focus on fine‐grained and coarse‐grained features, resulting in higher prediction accuracy. MAOOA is used to find a better quasi‐optimal hyperparameters for Residual‐Attitude‐BiConvLSTM. This paper provides a new approach for building TEC prediction models. At the same time, this study also indicates that in TEC prediction, in addition to focusing on designing prediction models with higher accuracy, attention should also be paid to the optimization algorithms of the models. Key Points: Proposed multi‐strategy assisted Osprey optimization algorithmuses three new strategies to boost its optimization capabilityNew TEC model Residual‐Attention‐BiConvLSTM improves feature retention and predictionMAOOA‐Residual‐Attention‐BiConvLSTM, a novel TEC prediction framework, merges deep learning with hyper‐parameter optimization [ABSTRACT FROM AUTHOR]

This paper investigates time‐lag effects of ionospheric response to two severe geomagnetic storms (Kp = 8) on the degradation of kinematic precise point positioning (PPP) solutions, utilizing over 5500 Global Navigation Satellite Systems (GNSS) stations distributed worldwide. Focusing on these two severe geomagnetic storms that occurred during solar cycle 24, the study employs an open‐source positioning software package, namely RTKLIB, to derive the PPP solutions. The findings reveal significant variations in time lags across different magnetic latitudes. These variations are driven by ionospheric responses to a southward interplanetary magnetic field and subsequent decreases in the SMY‐H index during the 2015 St. Patrick's Day Storm and the 2017 September 7–8 Storm. Specifically, at high latitudes, PPP degradation primarily manifests during the main phase of the storm, resulting in delays spanning from several minutes to 1–2 hr after the sudden onset of the storm. In contrast, mid‐ and low latitudes exhibit a wider range of delays extending up to tens of hours. Notably, rapid positioning degradation is observed predominantly at the magnetic local time noon and midnight sectors. The study discusses these time lag effects concerning the intensity of various ionospheric disturbances triggered by the interactions among the solar wind, magnetosphere, and ionosphere during geomagnetic storms. The insights obtained from this research have the potential to be integrated into physics‐based and machine‐learning models to enhance forecasting capabilities of space weather impacts. Plain Language Summary: This paper presents space weather impact on Global Navigation Satellite Systems positioning solutions. Specifically, it examines the time‐lag effects of the ionospheric response to severe geomagnetic storms. The study finds that the time it takes the positioning system to degrade varies depending on the device latitude. At high latitudes, the degradation happens quickly, within minutes to an hour after the storm starts. At mid‐ and low latitudes, the degradation takes longer, sometimes up to tens of hours after the storm onset. The differences in the time lag are related to how the ionosphere reacts to changes in the Earth's magnetic fields during these storms. This study is significant because it quantifies the time difference between the start of a storm and the degradation in the positioning system. The information gained from this research will help improve forecasting space weather impacts. Key Points: Initial attempt to quantify the time lags between the sudden onset of a geomagnetic storm and the degradation in precise point positioning on a global scaleTime lags in high latitudes typically vary from a few minutes to less than 2 hrMiddle and low latitudes responses show a wider range of time lags of up to several tens of hours [ABSTRACT FROM AUTHOR]

A lightweight, high‐definition vector map (HDVM) enables fully autonomous vehicles. However, the generation of HDVM remains a challenging problem, especially in complex urban scenarios. Moreover, numerous factors in the urban environment can degrade the accuracy of HDVM, necessitating a reliable error quantification. To address these challenges, this paper presents an open‐source and generic HDVM generation pipeline that integrates the global navigation satellite system (GNSS), inertial navigation system (INS), light detection and ranging (LiDAR), and camera. The pipeline begins by extracting semantic information from raw images using the Swin Transformer. The absolute 3D information of semantic objects is then retrieved using depth from the 3D LiDAR, and pose estimation from GNSS/INS integrated navigation system. Vector information (VI), such as lane lines, is extracted from the semantic information to construct the HDVM. To assess the potential error of the HDVM, this paper systematically quantifies the impacts of two key error sources, segmentation and LiDAR‐camera extrinsic parameter error. An error propagation scheme is first formed to illustrate how these errors fundamentally influence the accuracy of the HDVM. The effectiveness of the proposed pipeline is demonstrated through our codeavailable at https://github.com/ebhrz/HDMap. The performance is verified using typical datasets, including indoor garages and complex urban scenarios. [ABSTRACT FROM AUTHOR]

Various types of Global Navigation Satellite System (GNSS) data are used for a wide range of applications. When modeled correctly, millimeter precision daily GNSS position time‐series yield velocities and other derived products that can be used for investigations of lithospheric processes and properties. In this review paper, we describe the specific types of GNSS data and data products that are valuable for studies of the lithosphere, such as coseismic offsets, post‐seismic decay in time‐series, seasonal signals, secular velocities, and strain rates, and how those data are derived. We also discuss the applications of several types of GNSS data and data products. We provide open access resources for precision GNSS daily position time‐series, quality secular velocity solutions, and daily GNSS RINEX files for researchers interested in processing their own data. Plain Language Summary: Measurements of how the surface of the Earth moves can be made with millimeter precision using Global Navigation Satellite System (GNSS) data. Several different types of GNSS‐derived data can be used to study the relatively rigid outer layers of the Earth known as the lithosphere. In this review paper, we detail how GNSS data that are relevant for lithospheric studies are determined, including what corrections and errors must be considered. We describe several applications of certain GNSS data, such as quantifying tectonic plate motions. At the end of the paper, we provide numerous open access resources for GNSS data and data products that are valuable for studies of the Earth's lithosphere. Key Points: Describe various types of Global Navigation Satellite System (GNSS) data and their uses for studying the lithosphereReview of the treatment of GNSS data required for lithospheric studiesProvide information about numerous open access GNSS data resources [ABSTRACT FROM AUTHOR]

The significant risk associated with fault reactivation often necessitates slip tendency analyses for effective risk assessment. However, such analyses are challenging, particularly in large areas with limited or absent reliable stress measurements and where the cost of extensive geomechanical analyses or simulations is prohibitive. In this paper, we propose a novel approach using a physics‐informed neural network that integrates stress orientation and satellite displacement observations in a top‐down multi‐scale framework to estimate two‐dimensional slip tendency analyses even in regions lacking comprehensive stress data. Our study demonstrates that velocities derived from a continental scale analysis, combined with reliable stress orientation averages, can effectively guide models at smaller scales to generate qualitative slip tendency maps. By offering customizable data selection and stress resolution options, this method presents a robust solution to address data scarcity issues, as exemplified through a case study of the South Australian Eyre Peninsula. Plain Language Summary: Fault reactivation poses significant risks, often requiring slip tendency analyses for thorough risk assessment. Yet, such analyses face challenges, especially in large areas lacking reliable stress measurements or where extensive geomechanical analyses are too costly. Our paper suggests a new method using a physics‐based neural network. This approach combines compressive direction and satellite displacement observations to estimate slip tendencies in two dimensions, even where stress data is lacking. Our study shows that by using displacements from a continental scale analysis and reliable averages of compressive directions, we can guide models to create smaller‐scale maps indicating where faults are more likely to reactivate. This method allows for customizable data selection and stress resolution, offering a strong solution to data scarcity issues. We demonstrate its effectiveness through a case study of South Australia's Eyre Peninsula. Key Points: Physics‐based neural networks allow two‐dimensional slip tendency analyses without prior full‐stress informationA multi‐scale approach provides required displacement constraints when inferring full stresses from global navigation satellite system (GNSS) and stress orientation dataWe present a new application for GNSS data that would welcome more stations, even in seismically stable areas [ABSTRACT FROM AUTHOR]

This paper studies a new concept of using global navigation satellite system (GNSS) signals coherently reflected over relatively smooth ocean and ice surfaces from very low elevation angles (below ∼8°) and received by low Earth orbit (LEO) satellites to retrieve the tropospheric information. This approach can provide horizontal profiles of tropospheric zenith delay and total column water vapor (TCWV) with centimeter‐level high precision and spatial resolutions of tens of km by ∼1 km, depending on the elevation angle, with a sampling spacing of ∼100 m. This approach can potentially be applied to most sea ice and calm ocean areas and provide tropospheric sensing data, which can complement and augment existing observation systems. A few case studies are conducted in this paper using the Spire grazing‐angle GNSS‐R data. The retrieved TCWV is compared to ERA5 products and the Sentinel‐3 Ocean and Land Color Instrument measurements and shows promising performances. The errors associated with the GNSS‐R tropospheric measurements are also discussed. Plain Language Summary: The atmospheric water vapor is an important component for the weather and climate systems and is difficult to measure, especially over ocean and ice surfaces. This paper studies a new approach to measuring atmospheric water vapor using global navigation satellite system (GNSS) signals reflected off ocean and ice surfaces. If the reflection is from a low elevation angle (below ∼8°) and the reflected signal is coherent (all signal rays are reflected in the same direction), this approach can provide very high precision observation of the horizontal gradients of the tropospheric delay and the vertically integrated atmospheric water vapor with good spatial resolutions. This paper presents the methodology of the proposed approach and a few case studies to demonstrate the feasibility and performance by comparing the GNSS‐R retrieved water vapor measurements with models and the Sentinel‐3 satellite radiometry measurements. The errors associated with the GNSS Reflectometry (GNSS‐R) tropospheric measurements are also discussed. Key Points: A new tropospheric sensing concept is studied that relies on coherent‐reflection global navigation satellite system (GNSS) signals off ocean and ice surfacesAlgorithms are developed and demonstrated using Spire grazing‐angle GNSS‐R data to retrieve tropospheric delay and water vaporThe presented approach provides high‐precision tropospheric delay and total column water vapor horizontal profiles, as validated using the Sentinel‐3 Ocean and Land Color Instrument data [ABSTRACT FROM AUTHOR]

In this paper, we propose a novel Total Electron Content (TEC) map prediction model, named ED‐AttConvLSTM, using a Convolutional Long Short‐Term Memory (ConvLSTM) network and attention mechanism based on encoder‐decoder structure. The inclusion of the attention mechanism enhances the efficient utilization of spatiotemporal features extracted by the ConvLSTM, emphasizing the significance of crucial spatiotemporal features in the prediction process and, as a result, leading to an enhancement in predictive performance. We conducted experiments in East Asia (10°N–45°N, 90°E−130°E). The ED‐AttConvLSTM was trained and evaluated using the International GNSS Service TEC maps over a period of six years from 2013 to 2015 (high solar activity years) and 2017 to 2019 (low solar activity years). We compared our ED‐AttConvLSTM with IRI‐2016, COPG, LSTM, GRU, ED‐ConvLSTM and ED‐ConvGRU. The results indicate that our model surpasses the comparison models in forecasting both high and low solar activity years, across most months and UT moments in a day. Moreover, our model exhibits notably superior prediction performance during the most severe phases of a magnetic storm when compared to the comparison models. Subsequently, we then also discuss how the prediction performance of our model is affected by latitude. Finally, we discuss the diminishing performance of our model in multi‐day predictions, demonstrating that its reliability for forecasts ranging from one to 4 days in advance. Beyond the fifth day, there is a pronounced decline in the model's performance. Plain Language Summary: High precision prediction of Total Electron Content (TEC) is of great significance for improving the accuracy of global satellite navigation systems. In this paper, we introduced the attention mechanism into the ionospheric TEC map prediction model to adaptively weight the ionospheric TEC spatiotemporal features, highlighting the contribution of important spatiotemporal features in TEC map prediction. Results showed that the prediction performance of our model is improved compared with the other six models. Key Points: Introducing ED‐AttConvLSTM, a novel Total Electron Content (TEC) map prediction model utilizing Convolutional Long Short‐Term Memory and an attention mechanism in an encoder‐decoder frameworkThe incorporation of attention mechanisms markedly decreased root mean square error in TEC map predictions for 2015 and 2019Our model excels over 6 state‐of‐the‐art models, affirming its robustness and reliability for TEC map prediction [ABSTRACT FROM AUTHOR]

The Macau Science Satellites (MSS‐1) mission, consisting of twin low earth orbit satellites (Satellite A and B), is the first low‐inclination and high‐precision geomagnetic surveying satellite project in China. Among the multiple scientific payloads equipped with the scientific satellites, MSS‐1 carries a GNSS radio occultation (RO) receiver on Satellite A, and aims to observe the Earth's ionosphere and monitor the space weather especially in the South Atlantic Anomaly (SAA) area. This paper focuses on the ionospheric data of MSS‐1 obtained during the first 3 months after its launch, and assesses the RO products as well as initial scintillation measurements. Results show that MSS‐1 RO data have very good agreement with contemporary COSMIC‐2 and ionosonde observations. The scintillation amplitude indices S4 are comparable with that of COSMIC‐2 and well reflect the occurrence rates and distributions of equatorial plasma bubble and sporadic E (Es) in June solstice season. Special attentions are paid to the SAA longitude sector and inspire explorations on the seasonal variations and local‐time dependences of ionospheric irregularities. Key Points: The MSS‐1 ionospheric radio occultation products are comparable with COSMIC‐2 and ionosondesScintillation characteristics in the June solstice season are well reflected based on MSS‐1 high‐rate measurements [ABSTRACT FROM AUTHOR]

Low latitude ionosphere experiences complex dynamical and electrodynamical processes, which make the spatiotemporal variations of the corresponding electron density complicated and therefore influence trans‐ionosphere radio communications. The monitoring of low latitude dynamical drivers, such as neutral wind and ionospheric electric field, is essential for both dynamic mechanism investigations and applications. The Sanya Incoherent Scatter Radar Tristatic System (SYISR‐TS) was proposed with the main objective of low latitude ionospheric monitoring and investigation and has been successfully developed over the past decade. The system consists of the Sanya (18.3°N, 109.6°E) trans‐receiving main station with key parameters of ∼1,600 m2 antenna aperture, >4 MW peak power, <120 K system noise temperature, and ∼46 dBi normal gain, and Danzhou (19.5°N, 109.1°E) and Wenchang (19.6°N, 110.8°E) receiving only stations with key parameters of ∼790 m2 antenna aperture, <130 K system noise temperature, and ∼43 dBi normal gain. Three stations form a quasi‐equilateral triangle at Hainan Island and use Global Navigation Satellite System satellite common view technique to achieve the time synchronization with the uncertainty of the timing and time synchronization less than 50 and 10 ns, respectively. Initial collaborative satellite tracking and ionospheric common volume experiments among three stations have confirmed the detection ability of SYISR‐TS and the feasibility of achieving its scientific goals in the future. Plain Language Summary: Ionosphere is the ionized part (electrons and ions) of upper atmosphere around 60–1,000 km altitude. In the ionosphere, the generation and movement of electrons and ions are jointly determined by the solar radiation, photo‐chemistry, winds and electric fields. Monitoring the density of electrons, and winds and electric fields as well, is important for understanding and predicting the status of ionosphere. Among numerous ionospheric detection methods, Incoherent Scatter Radar (ISR) plays an important role due to its profiling multiple parameters capability. In this paper, we will describe the technical details and initial experiments of the newly built Sanya Incoherent Scatter Radar Tristatic System. It is also the world first tristatic ISR system using phased array technology, which can switch the beam direction quickly therefore increase the time resolution of measurements significantly. Key Points: Sanya Incoherent Scatter Radar Tristatic System (SYISR‐TS) is the world first completed phased array based tristatic ISR systemSYISR‐TS includes 1 trans‐receiving and 2 remote receiving stations and uses Global Navigation Satellite System satellite common view technique to achieve synchronizationInitial collaborative experiments among three stations have confirmed the detection ability of SYISR‐TS [ABSTRACT FROM AUTHOR]

Culverwell et al. (2023, https://doi.org/10.1029/2023SW003572) described a new one‐dimensional variational (1D‐Var) retrieval approach for ionospheric GNSS radio occultation (GNSS‐RO) measurements. The approach maps a one‐dimensional ionospheric electron density profile, modeled with multiple "Vary‐Chap" layers, to bending angle space. This paper improves the computational performance of the 1D‐Var retrieval using an improved background model and validates the approach by comparing with the COSMIC‐2 profile retrievals, based on an Abel Transform inversion, and co‐located (within 200 km) ionosonde observations using all suitable data from 2020. A three or four layer Vary‐Chap in the 1D‐Var retrieval shows improved performance compared to COSMIC‐2 retrievals in terms of percentage error for the F2 peak parameters (NmF2 and hmF2). Furthermore, skill in retrieval (compared to COSMIC‐2 profiles) throughout the bottomside (∼90–300 km) has been demonstrated. With a single Vary‐Chap layer the performance is similar, but this improves by approximately 40% when using four‐layers. Plain Language Summary: Culverwell et al. (2023, https://doi.org/10.22541/essoar.168614409.98641332) presented a new way of estimating ionospheric electron density using the amount of bending experienced by GNSS signals in the upper atmosphere. In this paper, as well as providing extensive validation of the technique, the computational performance is improved by using better initial conditions. The validation is done by comparing the newly described approach with the method used by the COSMIC‐2 satellite constellation using additional data from ground‐based sensors known as ionosondes. The newly described technique is found to provide improvements of approximately 40% compared to a complementary approach using by COSMIC‐2. Key Points: Improved computational performance of the 1D‐Var bending angle retrieval is demonstrated with a better background modelExtensive validation of the 1D‐Var retrieval approach compared to ionosonde and Abel‐inversion‐based COSMIC‐2 retrievals has been undertakenThe 1D‐Var retrieval, using four‐layers, is shown to have an 40% reduction in root mean square error compared to COSMIC‐2 retrievals [ABSTRACT FROM AUTHOR]

Geomagnetic storms induce ionospheric disturbances, affecting short‐wave radio communication systems. Accurate ionospheric total electron content (TEC) prediction is vital for accurately describing the short‐wave radio environment of the ionosphere. We use the Multi‐Step Auxiliary Prediction (MSAP) model, a deep learning algorithm, to forecast TEC during geomagnetic storms. The MSAP model integrates Bi‐LSTM networks, an auxiliary model, and convolutional processes for spatiotemporal modeling. Our validation shows the MSAP model outperforms the IRI‐2016 model in predicting global TEC for the next 6 days in the test set. We assess its performance during 116 geomagnetic storm events, considering storm intensity, solar activity, month, and Universal Time (UT). The MSAP model exhibits a weak correlation with storm intensity and a strong correlation with solar activity. Monthly variation displays similar strong correlations in root mean square error (RMSE) and R2 for both models. For UT variation, the other metrics exhibit a weak correlation with the number of Global Navigation Satellite System stations, except for the RMSE of the MSAP and IRI‐2016 models. Plain Language Summary: Total electron content (TEC) is an important parameter to describe the ionosphere. The prediction of TEC is crucial for short‐wave communication systems. Geomagnetic storms disturb the ionosphere, thereby affecting the prediction of TEC. In this paper, the existing multi‐step auxiliary prediction model is used to predict the TEC during geomagnetic storms. Using the International Reference Ionosphere‐2016 model as the reference, the storm‐time performance and time‐varying characteristics of Multi‐Step Auxiliary Prediction (MSAP) are studied. It is found that the MSAP model captures variations with solar activity, month, and Universal Time during geomagnetic storms. Key Points: The MSAP model can predict total electron content (TEC) with high accuracy and stabilityThe MSAP model perform differently in different phases of geomagnetic storms [ABSTRACT FROM AUTHOR]

Two subsequent World Radiocommunication Conferences, held in 2015 and 2019, have concluded the frequency allocation in VHF bands for the two-way maritime VHF Data Exchange System (VDES) via terrestrial and satellite radio frequency links respectively. Although primarily a terrestrial system, VDES also allow for satellite use.[[1]] In particular, the VDE has defined both a terrestrial component (VDE-TER) and a satellite component (VDE-SAT). As they could not all be accommodated by ASMs, the concept of VHF Data Exchange (VDE) was defined and the VHF Data Exchange System (VDES) was born. [Extracted from the article]

The Hunga Tonga‐Hunga Ha'apai (hereafter HTHH) submarine volcano erupted at 04:14:45 UT on 15 January 2022, causing ionospheric disturbances. This paper uses carrier phase observations from GNSS tracking stations in New Zealand and Australia to calculate the vertical total electron content. At 06:10, the ground‐based GNSS tracking station in New Zealand observes a maximum amplitude of 2.26 TECU anomaly caused by a mesoscale traveling ionospheric disturbance (MSTID) with a wavelength of 200–250 km, a period of 6–13 min, and a maximum propagation velocity of 330 m/s. The anomaly developed with time along the north‐south island direction toward the south island and lasted for about three and a half hours, with the ionosphere returning to pre‐eruption levels after 09:50, indicating a correlation between ionospheric activity and volcanic eruption. An ionospheric anomaly caused by an MSTID was also observed off the east coast of Australia around 08:11, with a maximum amplitude of 3.17 TECU and a maximum propagation velocity of 356 m/s. The ionospheric anomaly in Australia spreads out in a plane. In the process of propagation, it continuously impacts the area it passes through, and the entire anomaly process lasts for more than 7 hr. Still, the anomalous propagation velocities are more significant than in New Zealand, indicating that the Lamb waves excited by the eruption of the HTHH submarine volcano are directional in propagation speed; westward travels faster than southward. This finding will provide more references for scholars to study the mechanism and characteristics of anomaly propagation. Plain Language Summary: This paper reports on the Hunga Tonga‐Hunga Ha'apai submarine volcanic eruption event at Tonga on 15 January 2022, which caused air pressure waves in the form of Lamb waves to propagate to ionospheric heights and caused traveling ionospheric disturbances. Analysis of the filtered total electron content in the ionosphere using dense GNSS tracking stations in Australia and New Zealand revealed large‐scale, intense ionospheric disturbances. The propagation of the anomaly is also directional, with the New Zealand ionospheric anomaly initially propagating from north to south in a ripple pattern with a maximum mesoscale traveling ionospheric disturbance (MSTID) propagation velocity of ∼330 m/s. The impact of Lamb waves on the ionosphere in Australia is more pronounced, with the disturbance unfolding in a faceted pattern from east to west for up to 7 hr, during which the maximum MSTID propagation velocity is ∼356 m/s. In addition, the anomaly is affected by small‐amplitude gravity waves and excites multiple ionospheric disturbance phenomena during its propagation in both locations. This result confirms the natural phenomenon of ionospheric disturbances induced by extreme natural hazards and shows that severe explosive events can have a lasting and far‐reaching impact on the ionosphere. Key Points: Evidence of widespread traveling ionospheric disturbances caused by volcanic eruptionsThe propagation of the anomaly is directional, propagating westward at a greater rate than southwardSmall‐scale gravity waves have caused multiple transient ionospheric disturbances in both New Zealand and Australia [ABSTRACT FROM AUTHOR]

Literature shows that only 56% of Kenyan households had access to electricity, with rural areas having the lowest access rate at percent. The high cost of extending the power grid to remote areas and power losses on distribution are significant challenges facing rural electrification. In addressing power accessibility problems, especially in rural areas, there is a need for tapping hydropower generation through the invention and implementation of in‐duct turbines to maximize the utilization of already existing pressurized water ducts that supply water in various parts of Kenya for hydropower generation. Makueni County is endowed with gravity‐fed water ducts with high potential for hydropower which can innovatively be produced by application of in‐duct turbines. This paper focuses on the assessment of energy needs and applications in rural areas. The research design was exploratory and experimental in nature. It was exploratory because, through an assessment, it sought to explore and identify the potential areas within the water supply lines for the production of hydropower to supply hydropower in Makueni County. It was experimental because the researcher developed (designed and fabricated) a hydro turbine for use in the production of hydropower from gravity water ducts of a diameter raging 100 mm. The research revealed that 62% (98) used solar power for lighting their homes, while 17% (28), 12% (20), and 8% (12) used lanterns, electricity, and kerosene lamps, respectively. Among the fuels assessed was firewood which was identified as the most used fuel at 89% (140). This was followed at a distance far by paraffin at 6% (9) of respondents. The households at 100% (158) identified electricity as a potential source of lighting for their household. The study recommends harnessing hydropower to enhance reach to 100% of the rural communities. The energy availability will provide opportunities for communities and institutions in rural areas to open their minds to business development and engage in income‐generating activities like the rearing of poultry and the development of light industries like the gridding of maize and other cereals. [ABSTRACT FROM AUTHOR]

The UC Berkeley Random Walk Algorithm WaterMask from CYGNSS (Berkeley‐RWAWC) is a new data product designed to address the challenges of monitoring inundation in regions hindered by dense vegetation and cloud cover as is the case in most of the Tropics. The Cyclone Global Navigation Satellite System (CYGNSS) constellation provides data with a higher temporal repeat frequency compared to single‐satellite systems, offering the potential for generating moderate spatial resolution inundation maps with improved temporal resolution while having the capability to penetrate clouds and vegetation. This paper details the development of a computer vision algorithm for inundation mapping over the entire CYGNSS domain (37.4°N–37.4°S). The sole reliance on CYGNSS data sets our method apart in the field, highlighting CYGNSS's indication of water existence. Berkeley‐RWAWC provides monthly, low‐latency inundation maps starting in August 2018 and across the CYGNSS latitude range, with a spatial resolution of 0.01° × 0.01°. Here we present our workflow and parameterization strategy, alongside a comparative analysis with established surface water data sets (SWAMPS, WAD2M) in four regions: the Amazon Basin, the Pantanal, the Sudd, and the Indo‐Gangetic Plain. The comparisons reveal Berkeley‐RWAWC's enhanced capability to detect seasonal variations, demonstrating its usefulness in studying tropical wetland hydrology. We also discuss potential sources of uncertainty and reasons for variations in inundation retrievals. Berkeley‐RWAWC represents a valuable addition to environmental science, offering new insights into tropical wetland dynamics. Plain Language Summary: The UC Berkeley Random Walk Algorithm WaterMask from CYGNSS (Berkeley‐RWAWC) is a new data product developed to better monitor areas that are hard to observe due to thick vegetation and clouds, such as tropical regions. Using data from the Cyclone Global Navigation Satellite System (CYGNSS), an 8‐satellite constellation, Berkeley‐RWAWC has more frequent data collection compared to single‐satellite systems. This allows mapping of flooding or water accumulation with improved accuracy over time, even in clouds‐prone and overgrown areas. Berkeley‐RWAWC spans from 37.4° North to 37.4° South and consists of monthly inundation maps at approximately 1 km by 1 km resolution since August 2018. The method places the greatest emphasis on CYGNSS data indications of where is the water, making it different from others. In this paper, we explain how we made the maps, and compare them with other data sets in four different areas: the Amazon Basin, the Pantanal, the Sudd, and the Indo‐Gangetic Plain. Our comparisons show that Berkeley‐RWAWC is better at showing how water changes with the seasons, which is useful for understanding tropical wetland water cycles. Berkeley‐RWAWC is publicly available and can become an important new resource for studying our planet, especially in the study of patterns in tropical wetlands. Key Points: Vegetation and clouds can obstruct the view of waterbodies, making accurate, seasonal mapping difficultThis new CYGNSS‐based product combines L‐band microwaves with computer vision to produce quasi‐global monthly maps of waterbodiesThe product shows greater seasonal and interannual variability than other data sets for new insights into tropical hydrological processes [ABSTRACT FROM AUTHOR]

Accurate positioning of intelligent connected vehicle (ICV) is a key element for the development of cooperative intelligent transportation system. In vehicular networks, lots of state‐related measurements, especially the mutual measurements between ICVs, are shared. It is an advisable strategy to fuse these measurements for a more robust positioning. In this context, an innovative framework, referred to as multisource‐multitarget cooperative positioning (MMCP) is presented. In MMCP, ICVs are local information source, that upload both the states of ICVs estimated by on‐board sensors and the relative vectors between surrounding objects and vehicles to a fusion centre. In the fusion centre, ICVs are selected as the global targets, and the relative vectors are converted into global measurements. Then, the MMCP is modelled into a multi‐target tracking problem with specific targets. This paper proposes a low complexity Gaussian mixture probability hypothesis density (GM‐PHD‐LC) filter to match and fuse the global measurements to further improve the estimation of ICVs. The evaluation results show that our GM‐PHD‐LC can provide 10 Hz positioning services in urban area, and significantly improve the positioning accuracy compared to the standalone global navigation satellite system. [ABSTRACT FROM AUTHOR]

Ionospheric delay, as one of the largest error sources in radio propagation, can only be corrected for this error using the ionospheric delay correction model for Global Navigation Satellite System (GNSS) single‐frequency users. In this paper, the 2021 geomagnetic storm event is selected, and based on the measured ionospheric data from the GNSS observatory, the perturbation of the ionosphere by the geomagnetic storm event is analyzed, and it is found that the response of the ionosphere to the geomagnetic storm has obvious differences in the response characteristics and response time in different latitude regions. The performance of the global ionospheric map (GIM), the empirical model, and the broadcast ionospheric model during the geomagnetic storm‐induced ionospheric perturbation is analyzed and the change in the accuracy of each ionospheric model during the geomagnetic storm‐induced ionospheric perturbation is investigated, using the measured electron content of the GNSS as a benchmark. The results show that there is good agreement between the GIM products and the measured electron content during the period of ionospheric calm and the period of ionospheric perturbation. It is worth noting that geomagnetic storms do not necessarily lead to a decrease in the accuracy of ionospheric delay‐correction models, and in some cases, the models that were originally under‐accurate show a tendency to improve their accuracy during the period of perturbation instead. Neither the broadcast ionospheric model nor the electron content of the empirical model output responds to geomagnetic storm‐induced ionospheric perturbations. Plain Language Summary: The change characteristics of the ionosphere during geomagnetic storms are very complex. In this paper, we study the characteristics of ionospheric changes during geomagnetic storms and the performance of models during ionospheric perturbations. The results show that the ionospheric characteristics at different latitudes during geomagnetic storms are very different; and there is a phenomenon that the accuracy of the model correction is improved during the perturbation of geomagnetic storms. This paper provides a reference for improving the performance enhancement and application of ionospheric delay correction models. Key Points: Ionospheric disturbances caused by geomagnetic storms have different spatial and temporal characteristicsGlobal ionospheric map has the optimal performance in the calm period and the perturbation periodThe broadcast ionospheric model and the empirical model do not respond to ionospheric perturbations [ABSTRACT FROM AUTHOR]

This paper investigates the effects of a minor G1 Co‐rotating Interaction Region (CIR)/High‐Speed Stream (HSS)‐driven geomagnetic storm that occurred on (13–14 October 2018), during deep solar minimum. We used simultaneous observations from multiple instruments, namely; ground‐based Global Navigation Satellite Systems (GNSS) receivers, a Digisonde, ground magnetometers, and space‐based observations from the National Aeronautics and Space Administration Global‐scale Observations of Limb and Disk (GOLD) and SWARM missions. This study presents a detailed picture of the low‐latitude ionosphere response over the Brazilian sector during a minor storm. Our results showed that the minor CIR/HSS‐driven storm caused a positive ionospheric storm of over ∼20 TECU in magnitude. For the first time, periodic post‐sunset irregularities and Equatorial Plasma Bubbles, equatorial plasma bubbles, were analyzed using GOLD FUV OI 135.6 nm emission, Total Electron Content (TEC) maps, Rate of TEC index, ROTI, and TEC gradients. Fluctuations in the interplanetary magnetic field Bz and changes in the thermospheric column density ratio (∑O/N2) are discussed as the main sources of ionospheric changes during the storm. This paper highlights the importance of monitoring and understanding the impact of Sun‐Earth interactions and provides insight into the behavior of the low‐latitude ionosphere during minor geomagnetic storms. Plain Language Summary: Solar activity has been steadily declining over the past 4 solar cycles, in particular, the solar minima of Cycles 23 and 24 (2008–2009 and 2018–2019), were unusually weak in terms of solar activity. This period of low solar activity called deep Solar Minimum, provides a unique opportunity to study the behavior of the Earth's atmosphere and its interactions with the sun. Although the solar minimum of SC24 had much fewer sunspots than usual, which are the source of intense geomagnetic storms, fast solar wind streams or High‐Speed Streams (HSSs) were still present. HSSs interact with the slower‐moving wind, causing weak‐to‐moderate geomagnetic storms which have significant impact on the Geospace. These storms affect the Total Electron Content and plasma gradients in the ionosphere, which are important sources of errors and failures in positioning and navigation such as Global Navigation Satellite Systems and GBAS systems. This article discusses the effects of a minor geomagnetic storm during a deep solar minimum in 2018 on the Brazilian low‐latitude ionosphere. Key Points: A minor Co‐rotating Interaction Region/High‐Speed Stream storm triggered a large positive ionospheric storm during deep solar minimumMulti‐scale, periodic plasma irregularities were detectedFirst characterization of equatorial plasma bubbles (EPBs) over Brazil using space‐borne Global‐scale Observations of Limb and Disk (GOLD) FUV 135.6 nm images and ground‐based instruments [ABSTRACT FROM AUTHOR]

In this paper, we propose the usage of an ensemble learning approach for predicting total electron content (TEC). The training data set spans from 2007 to 2016, while the testing data set is set to the year 2017. The model inputs in our study included Solar radio flux (F107), Solar Wind plasma speed, By, Bz, Dst, Ap, AE, day of year, universal time, 30‐day and 90‐day TEC averages. Specifically, eXtreme Gradient Boosting (XGBoost), Gradient Boosting Decision Tree, and Decision Tree were utilized for 1‐hr TEC prediction at high‐ (80°W, 80°N), mid‐ (80°W, 40°N), and low‐ latitudes (80°W, 10°N). Results indicate that all three models performed well in predicting TEC, with a mean error of only approximately 0.6 TECU at high‐ and mid‐ latitudes and 1.13 TECU at low latitudes. At the same time, we compared the model with 1‐day Beijing University of Aeronautics and Astronautics model during the period of magnetic storm from 25 August 2018 to 27 August 2018 and a quiet period from 13 December 2018 to 15 December 2018. In the magnetic storm period, Our model showed an average reduction of 1.83 TECU compared to BUAA model. During the quiet period, XGBoost exhibit an average error that is 1.14 TECU lower than that of BUAA model. Moreover, TEC prediction over the region between the 20°N–45°N and 70°E−120°E during geomagnetic storm has an error of 2.74 TECU, showing the stability and superiority of XGBoost. Overall, the ensemble learning approach exhibits its advantage in predicting TEC. Plain Language Summary: Due to the impact of the ionosphere on the propagation of radio waves and its significant influence on global navigation satellite systems, we have conducted modeling of the ionospheric total electron content (TEC), which describes the morphology and structure of the ionosphere. We propose the use of eXtreme Gradient Boosting (XGBoost), Gradient Boosting Decision Tree, and Decision Tree to predict TEC in different geographical latitudes. We also evaluate the best prediction time of the XGBoost model in a day. Additionally, the XGBoost model was tested during a geomagnetic storm, and TEC prediction over the region between 20°N and 45°N and 70°E−120°E showed the average error of 2.74 TECU, indicating its stability and superiority. Key Points: Three ensemble learning models are employed to predict total electron content (TEC) in various latitudes using data spanning a solar cycleeXtreme Gradient Boosting model has less predicted errors than Gradient Boosting Decision Tree and Decision Tree models, and the previous TEC history dominants the predicted TEC valuesThe RMSE increases with the predicted time advance, and the average relative error is the minimum in the mid‐latitude [ABSTRACT FROM AUTHOR]

This paper investigates the midlatitude ionospheric disturbances over the American/Atlantic longitude sector during an intense geomagnetic storm on 23 April 2023. The study utilized a combination of ground‐based observations (Global Navigation Satellite System total electron content and ionosonde) along with measurements from multiple satellite missions (GOLD, Swarm, Defense Meteorological Satellite Program, and TIMED/GUVI) to analyze storm‐time electrodynamics and neutral dynamics. We found that the storm main phase was characterized by distinct midlatitude ionospheric density gradient structures as follows: (a) In the European‐Atlantic longitude sector, a significant midlatitude bubble‐like ionospheric super‐depletion structure (BLISS) was observed after sunset. This BLISS appeared as a low‐density channel extending poleward/westward and reached ∼40° geomagnetic latitude, corresponding to an APEX height of ∼5,000 km. (b) Coincident with the BLISS, a dynamic storm‐enhanced density plume rapidly formed and decayed at local afternoon in the North American sector, with the plume intensity being doubled and halved in just a few hours. (c) The simultaneous occurrence of these strong yet opposite midlatitude gradient structures could be mainly attributed to common key drivers of prompt penetration electric fields and subauroral polarization stream electric fields. This shed light on the important role of storm‐time electrodynamic processes in shaping global ionospheric disturbances. Plain Language Summary: The storm‐time midlatitude ionosphere is a highly dynamic region that can exhibit much more pronounced electron density gradients and disturbances than expected. The combined data from ground‐based and satellite measurements provided valuable insights into the intricate behavior of the midlatitude ionosphere during an intense geomagnetic storm on 23 April 2023. The midlatitude ionosphere was characterized by significant electron density gradient structures, comprising both phenomenal density depletion and exceptional enhancements. Notably, a remarkable band‐like ionospheric super‐depletion structure was observed in local dusk, which extended to ∼40° geomagnetic latitude, corresponding to an altitude of ∼5,000 km above the geomagnetic equator. In contrast, a significant midlatitude ionospheric density enhancement plume appeared simultaneously in local afternoon, which exhibited a dynamic variation with its intensity being quickly doubled and halved in just a few hours. The synchronous occurrence of these striking yet opposing density gradients highlights the importance of electrodynamic effect driven by common key drivers of storm‐time perturbed electric fields. This underscores the complex and interconnected nature of the ionospheric response during intense geomagnetic storms. Key Points: The storm main phase was characterized by coincident nightside bubble‐like ionospheric super‐depletion structure (BLISS) and dayside storm‐enhanced density (SED)The BLISS manifested as a poleward/westward‐streaming channel and extended to ∼40 MLAT, corresponding to an APEX height of ∼5,000 kmThe SED plume experienced a dynamic variation with the plume intensity being quickly doubled and halved in just a few hours [ABSTRACT FROM AUTHOR]

The paper reports occurrences of postmidnight to early morning ionospheric depletions in total electron content (TEC) observed using the Low Earth Orbiting satellite beacon from Calcutta (22.57°N, 88.36°E geographic, and 32°N magnetic dip) situated around the northern crest of the equatorial ionization anomaly (EIA) in the Indian longitude sector for the period 2015–2016. These results are novel and contrary to the usual scenario of equatorial ionospheric irregularities being dominant during the early evening to pre‐midnight hours of equinoctial months. The TEC depletions, commonly called "bite‐outs," exhibit amplitudes of 1–2.5 TECU, with maximum depletion found near the northern crest of the EIA around subionospheric coordinates 25.8°N and 82.2°E. These bite‐outs exhibited seasonal variabilities, with maximum occurrences found during local summer months. The observed TEC depletions during postmidnight hours point toward irregularities, which are not generated over the magnetic equator and drifted along magnetic field lines. A case study of the observation of these ionospheric disturbances has also been presented across a spectrum of frequencies, namely 150 and 400 MHz (Low Earth Orbit satellites), 250 MHz (Geostationary satellites), and 1.5 GHz (GPS—Medium Earth Orbit satellites) to establish the presence of irregularities of different scale sizes even during postmidnight hours. Key Points: The paper reports occurrences of postmidnight to early morning ionospheric depletions in total electron content observed from Calcutta for the period 2015–2016The total electron content depletions exhibit amplitudes of 1–2.5 TECU, with more occurrences found during local summer months than equinoctial monthsIonization density irregularities affected transionospheric satellite links at 150 and 400 MHz for LEO, 250 MHz for geostationary VHF, and 1.5 GHz for GPS [ABSTRACT FROM AUTHOR]

The runoff change in a large river is significant for hydrological event monitoring, such as floods and droughts. In this paper, we attempt to invert the river flow change based on the surface displacements observed by the continuous global navigation satellite system (GNSS) stations in the Wuhan section of the Yangtze River (WYR). We establish a two‐dimensional model accounting for deformation from a line load in an elastic half‐space to estimate the annual water load change from the GNSS data. The results show that the inverted line load from the annual maximum displacement change observed by the GNSS is Ne=2.30×108N·m−1 ${N}_{e}=2.30\times {10}^{8}\mathrm{N}\cdot {\mathrm{m}}^{-1}$, which is in good agreement with the river load from the hydrological station. This paper demonstrates a low‐cost and practical method to river flow research in local areas, which is also a creative application for the GNSS. Plain Language Summary: The runoff change in large rivers is an important element for flood and drought monitoring. Hydrological stations are used to monitor the water load change. Because of the high cost of construction and maintenance, there are few hydrological stations in most areas, and the unpredictable noise of hydrological stations influences the stability and precision of the results. We use the vertical displacements observed by the global navigation satellite system (GNSS) to estimate the river load and find that the results agree with the calculated water load change from hydrological stations. Thus, the GNSS can be an alternative for runoff change research, with low cost and high efficiency. In this study, we find a new application for the GNSS to water runoff change in local areas. Key Points: We propose a new method for estimate the river load change using the continuous global navigation satellite system (GNSS) dataA simple two‐dimensional line load on Elastic half‐space can invert the river load with considerable accuracy in local areasThe forward modeling prove that the modeled displacement agrees with the observed displacement from the GNSS [ABSTRACT FROM AUTHOR]

The rate of total electron content index (ROTI) and loss of lock (LoL) from global navigation satellite system (GNSS) observations are an important data source for ionospheric scintillation study. However, there are certain limitations of these data in ionospheric scintillation study, and clearing these limitations is important to understand the results from these data. In this paper, the variation of the ionospheric scintillation is revisited based on LoL and ROTI from a spatial dense GNSS network in the low latitude region of China. Via a priori knowledge of scintillation morphology, the method to determine the baseline ROTI for discriminating quiet and disturbed conditions is provided, and the abnormal data of ROTI and LoL unrelated to ionosphere are found and eliminated. Results show that the data examination is necessary. Using the qualified ROTI and LoL, the morphological variations of ionospheric irregularities are revisited. The temporal variation of ROTI and LoL are generally consistent, but there are some discrepancies. The maximum LoL occurrence is at about 21:00 LT, it is between 20:00 and 23:00 LT for ROTI. For spatial distribution, both parameters reach maximum occurrence in the southwest direction, but LoL is more concentrated. The azimuth range of maximum occurrence is 180–190° for LoL and 210–220° for ROTI. Statistically, the correlation between LoL occurrence and ROTI value from observation of single GNSS station is relatively good when ROTI <5 TECU/min, but it becomes worse when ROTI >5 TECU/min. However, their correlation can be greatly improved when data are averaged among all the stations. Plain Language Summary: The rate of total electron content index (ROTI) and loss of lock (LoL) from global navigation satellite system (GNSS) observations are an important data source for ionospheric scintillation study. However, there are certain limitations of these data in ionospheric scintillation study, and clearing these limitations is important to understand the results from these data. In this paper, the variation of the ionospheric scintillation is studied based on a small regional geodetic GNSS receiver network in Hong Kong, China. Via a priori knowledge of scintillation morphology, the baseline ROTI for discriminating quiet and disturbed conditions is determined. The morphological variations of ionospheric irregularities are studied. Results show that the temporal variation and spatial distribution of ROTI and LoL are generally consistent, but there are some discrepancies. Correlation between ROTI and LoL for large ROTI from single GNSS station is not good. However, it can be improved when data are averaged among all the stations. Key Points: Rate of total electron content index (ROTI) threshold to represent irregularities using TEC with 5‐s rate is given based on a prior knowledge of scintillation in low latitudeThe temporal variation of ROTI and loss of lock (LoL) from global navigation satellite system are generally consistent, but the azimuth orientation of LoL and ROTI occurrence show obvious differenceCorrelation between LoL occurrence and ROTI value can be greatly improved when data are averaged using a spatially dense stations network [ABSTRACT FROM AUTHOR]

This paper realizes the evaluation and optimal decision of the spoofing effect on the global navigation satellite system (GNSS) under navigation countermeasures based on the game perspective, to overcome the limitations of current relevant research findings and maintain the secure application of the GNSS and maximize its defensive benefit during countering. An evaluation system based on the perspective of the game between spoofing strategies and defense measures is created to build the benefit matrix, which can solve the limitation in building a benefit matrix (the vital element in a game) that conforms to the confrontation‐oriented GNSS spoofing properties. Based on the built benefit matrix, a method integrating the grey expert‐based system with the hybrid evolutionary method is developed to realize quantifying the matrix and further make the optimal decision stably, which can solve the uncertainties of qualitative indices during quantifying and no global optimal solution for benefit equations deduced from the quantified matrix. Finally, based on various judgment principles, simulation and testing results verify the effectiveness of the obtained results and the superiority of the proposed method by comparing the results solved by the method in this paper with the results obtained by other decision‐making processing methods. [ABSTRACT FROM AUTHOR]

Water vapor plays an extremely important role in the monitoring and prediction of weather, and GNSS tomography can obtain 3D spatiotemporal change information and reliable water vapor profiles. In this paper, an improved global navigation satellite system (GNSS) tropospheric tomography technique using an ERA5 (the fifth generation ECMWF reanalysis) product is developed. First, the ERA5 product was adopted to analyze the spatiotemporal distribution of water vapor, and a water vapor density threshold defining the top of the tomography was determined; then, the height of the grid top (GT) of different seasons was obtained through linear fitting; finally, the water vapor value between GT and tropopause is constrained using the data of the ERA5 product as the initial value. The new method for using the ERA5 product to determine the height of the GT of the tomographic grid reduces the height of the top layer of the grid and increases the number of effective GNSS rays. Data from nine CORS stations in Hong Kong in 2019 were selected for experiments. The results showed that the new algorithm increased the number of effective satellite signals by 14%. In addition, the ERA5 data, the radiosonde data, and the COSMIC‐2 data were used as reference values. The accuracy of the water vapor density obtained by the algorithm was improved by 25%, 17% and 9%, respectively. [ABSTRACT FROM AUTHOR]

The adverse effect of the ionospheric scintillation on Global Navigation Satellite System (GNSS) requires scintillation monitoring on a global scale. Ionospheric Scintillation Monitoring Receivers (ISMR) are usually adopted to monitor scintillation, while they are not suitable for global monitoring due to the 50 Hz data collecting rate, which restricts the distribution. This paper proposes a new method to extract the phase scintillation index from each GNSS carrier with 1s‐sampling‐interval, mainly based on the cycle slip detection, the geodetic detrending and the wavelet transform, in which the optimal symmetry parameter and the time‐bandwidth product are determined with trial calculation. Taken the σϕ ${\sigma }_{\phi }$ index provided by ISMR as the reference, 1‐year observations are utilized to evaluate the scintillation monitoring performance of the extracted index regarding the correlation of the magnitude in each observation arc, the detected daily scintillation occurrence rate, the diurnal variation pattern of the ionospheric scintillation, the correlation between the scintillation occurrence rate and the space weather parameter, and the complementary cumulative distribution of the magnitudes. Compared to the performance of Rate of Total electron content Index, a higher consistency can be achieved between the extracted index and the σϕ ${\sigma }_{\phi }$ index, indicating the rationality of applying the proposed method in monitoring scintillations. The extracted scintillation index can be expected to introduce geodetic receivers operating at 1s‐sampling‐interval into the field of ionospheric scintillation monitoring on a global scale. Plain Language Summary: Small scale structures in the ionosphere will interfere with the amplitude and phase of the Global Navigation Satellite System (GNSS) signals passing through them. This phenomenon is called ionospheric scintillation, which can affect the positioning navigation and timing services of GNSS, calling for the need of monitoring ionospheric scintillations on a global scale. A special type of receiver, called Ionospheric Scintillation Monitoring Receiver (ISMR), is usually needed in ionosphere monitoring. However, due to the high sampling rate and price, the distribution of ISMR is limited, making it impossible to realize large‐scale ionospheric scintillation monitoring using only ISMR. In order to solve this problem, this paper proposes a new method to extract the scintillation index from the widely distributed geodetic receivers. Although the existing Rate of Total electron content Index (ROTI) can also use geodetic receivers for ionospheric scintillation monitoring, experiments based on long‐period observations collected in the Arctic region of the North America show that the extracted scintillation index can be more accurate than ROTI and the scintillation information on each carrier can be provided. The extracted scintillation index provides a basis for realizing global ionospheric scintillation monitoring and modeling in the future. Key Points: A new method is proposed to extract the scintillation index by applying cycle slip detection, geodetic detrending and wavelet transformThe scintillation index can be extracted from each carrier of the 1s‐sampling‐interval Global Navigation Satellite System observationsThe extracted scintillation index can provide a consistent performance in monitoring scintillation as that given by Ionospheric Scintillation Monitoring Receiver [ABSTRACT FROM AUTHOR]

Summary: There has been growing interest within the satellite navigation community in the possibility of delivering positioning and timing services from existing or emerging constellations of Low‐Earth Orbit communication satellites. At the same time, the international maritime community has been investigating the potential use of communication signals transmitted from shore‐based stations for positioning—a concept commonly referred to as 'ranging mode', or R‐Mode. The driving force for these developments is the desire to reduce the reliance on traditional Global Navigation Satellite Systems (GNSS). One of the technologies being considered for use in R‐Mode is the evolution of the Automatic Identification System (AIS) known as the Very High Frequency Data Exchange System (VDES). VDES has a terrestrial and a satellite component. The feasibility of using terrestrial VDES transmissions for ranging was studied in a previous publication by the authors. This paper builds on the previous study and extends its results to the satellite component of VDES. Statistical bounds on the ranging error are derived for all downlink waveforms currently being considered for use in satellite VDES and for several custom‐designed transmission formats. The analysis supports the feasibility of using both the existing and custom waveforms in ranging applications and points to related trade‐offs that will need to be considered in the design of satellite VDES R‐Mode systems. [ABSTRACT FROM AUTHOR]

Radio occultation (RO) by the Earth's atmosphere of the transmitted signals of the Global Navigation Satellite Systems' satellites has improved numerical weather prediction, has benefited atmospheric process studies, and benchmarked climate change by its strong traceability to the international definition of the second. Until now, research with RO has been isolated to the few centers that actually process the data and impracticable elsewhere because of limitations on data formats, organization and volume of the data, download bandwidth, and the lack of a database that can be queried before downloading data. We announce the availability of RO data in the Registry of Open Data of Amazon Web Services (AWS). RO data are freely available for download for the user and free to process and store for the manager of the repository. RO data as processed by the COSMIC Program Office at the University Corporation for Atmospheric Research, by the Radio Occultation Meteorology Satellite Application Facility (ROM SAF), by EUMETSAT, and by the NASA Jet Propulsion Laboratory are available beginning with calibrated (excess) phase, extending to bending angle and refractivity and to retrievals of pressure, temperature and water vapor. The same RO repository also contains a metadata database that permits simple querying, filtering, and download of data using a Python application programming interface provided by this same project. Four tutorial demonstrations are provided as jupyter notebooks to provide representative samples of code to perform common research activities with RO data, including database querying and analysis, inter‐center comparison of RO retrieval performance, and atmospheric process studies. Plain Language Summary: Radio occultation is a space‐based technique used to profile pressure, temperature, and water vapor in the Earth's atmosphere from the surface to the top of the stratosphere. It has unusual properties compared to other methods for measuring the atmosphere from space, particularly its powerful calibration and its astonishing vertical resolution, both made possible because it is based on a measurement of timing rather than radiance. This paper announces the availability of all Earth radio occultation (RO) data ever obtained (with a few small exceptions) from multiple data providers in the Registry of Open Data of Amazon Web Services. This repository of RO data is formulated to greatly ease access and manipulation of RO data to users anywhere in the world. It comes with tutorials on how the data can be accessed, downloaded, and analyzed in the form of jupyter notebooks. Key Points: A repository of all historical Earth Radio occultation (RO) data of the atmosphere is now freely accessible in the Amazon Web Services Registry of Open DataData are organized to enable common RO, atmospheric science, and climate science research by users anywhereRO sounding data are easily queried, subset, and downloaded through a Python package available by PyPI [ABSTRACT FROM AUTHOR]

The Green's function approach is well‐established and widely used for modeling the surface mass loading displacements. Global mean Green's functions (MGFs) are commonly applied without considering local variations of the crustal structure. Derived from the modified layered Earth structure, the local Green's functions (LGFs) are theoretically beneficial to generate more accurate deformation, since they consider interior information of the local crust. This paper analyzed the differences among MGFs from Gutenberg–Bullen A model and two sets of LGFs derived from modified PREM Earth models consolidating with two crust models TEA12 and CRUST1.0, hereafter called PREMTEA and PREMCRU, respectively. Utilizing MGFs and two sets of LGFs, we modeled the corresponding 3D atmospheric loading displacements for 984 ITRF2014 stations and compared them with the ITRF2014 residuals. The results show that LGFs from PREMTEA and PREMCRU perform well in further promoting scatter reduction for ∼72%, ∼56%, and ∼85% of stations for the Up, East and North components, respectively. The improvements for the North components are significant (up to 3.6%). In particular, stations in the east coastal areas of North America and the west edge of Greenland exhibit further promoting scatter reduction for the East components (up to ∼2.5%), while those located in west coastline of North America show better performance for the North components. Nevertheless, there are significant anomalies in northern Europe for PREMCRU, the mutation margin of which should be carefully considered when using a resolution higher than 1°. In the area around station MORP (358.31°W, 55.21°N, sited at coastline of Britain), we suggest using PREMTEA model. Plain Language Summary: In any location worldwide, we employ a consistent set of numbers, known as load Green's functions that characterize the elastic properties of the Earth, to model the deformation caused by mass transfer on Earth's surface, which is referred to as surface mass loading effects. Most research and data products adopt same set of global mean Green's functions for any location on Earth, which neglects the differences in elastic properties of various regions of the Earth, leading to modeling errors to some extent. This study aims to optimize the modeling using local load Green's functions, with the objective of obtaining results that are more theoretically valuable. "Local" means that the Green's functions for each site are derived from an Earth model that takes into account the local crustal structure. The modeled atmospheric loading displacements exhibit enhanced alignment with GNSS position time series. This, in turn, further elucidates that deformations can be more attributed to atmospheric loading. Moreover, the model shows improved performance in the horizontal components when compared to the vertical components. Key Points: Local load Green's Functions enable a more precise modeling of loading displacements than global mean Green's FunctionsThe modeled atmospheric loading displacements based on Local Green's Functions can improve scatter reduction of GNSS position time seriesTwo sets of local load Green's Functions, based on CRUST1.0 model and TEA12 model, are compared. We recommend TEA12 for European region [ABSTRACT FROM AUTHOR]

Nighttime medium‐scale traveling ionospheric disturbances (MSTIDs) have been generally observed by ground‐based instruments. However, they provide 2‐dimensional images over only a limited field of view and are not distributed globally. The ground‐based observations reported that MSTID wavefronts exhibit backward‐C shapes virtually straddling the dip equator. In situ plasma density measurements onboard individual satellites could overcome the limited coverage of ground‐based MSTID observations. But, most of those spacecrafts could obtain only 1‐dimensional profiles of plasma density, which leaves uncertain whether the observed perturbations generally have the characteristic directivity of MSTIDs. This paper addresses this knowledge gap by statistically investigating nighttime perturbations in the mid‐latitude topside ionosphere observed by tandem satellites, Swarm A and C. We cross‐correlate the plasma density profiles observed by Swarm A and C. The correlation coefficient tends to increase as the two spacecraft move closer, allowing us to derive the disturbances' directivity whenever the Swarm A and C observations are correlated significantly. The directivity statistics agree well with the backward‐C shape. Furthermore, the wavefront directions have clear dependence on magnetic latitudes while they are not as well aligned with local time, which is also consistent with previous reports on nighttime MSTIDs using ground‐based observations and computer simulations. Additionally, we demonstrate that the nighttime MSTIDs can increase the topside Rate Of Total electron content Index above Swarm. All the above‐mentioned results support that the nighttime mid‐latitude perturbations observed by Swarm can be identified as MSTIDs on the whole, which is the most important finding of this paper. Plain Language Summary: In this paper, we statistically study the characteristics of nighttime plasma perturbations in the mid‐latitude topside using Swarm satellites. Conventionally, observations of those midlatitude perturbations heavily relied on ground‐based facilities, such as global positioning system (GPS) receivers, All‐Sky Cameras, and radars, from which we can obtain 2‐dimensional (2D) images of the medium‐scale traveling ionospheric disturbances (MSTIDs). On the other hand, in situ plasma density measured onboard individual Low Earth Orbit (LEO) satellites, which can cover the whole globe, only provided 1‐dimensional (1D) profiles, making it difficult to investigate the 2D morphology of perturbations. With two satellites flying side by side, we can overcome the limitation of the LEO in situ observations, which is the topic of this study. The results show that the 2D morphology of the perturbations in the nighttime mid‐latitude topside ionosphere agrees with the known properties of MSTIDs reported in previous ground‐based studies: backward‐C shape virtually straddling the dip equator. We also demonstrate that the MSTIDs can perturb the total electron content above Swarm, which supports that MSTIDs can exist even above Swarm heights and that they can disturb radio communication between Swarm and GPS satellites. Key Points: Quasi 2‐dimensional snapshots of nighttime mid‐latitude topside perturbations are taken by Swarm satellites in tandemThe perturbation directions conform to the backward‐C shape straddling the dip equator, which is a well‐known characteristic of medium‐scale traveling ionospheric disturbancesThe in‐situ perturbations can also disturb topside total electron content above Swarm [ABSTRACT FROM AUTHOR]

In this paper, we study the problem of maintaining a stable mobile robot formation, steering and localizing all robots in an unknown dynamic environment consisting of multiple periodically moving objects, without the presence of a global positioning system or a robot tracking system. We propose a distributed observer such that each agent can estimate global positions of all mobile robots and that of moving landmarks in an unknown environment. By combining the proposed distributed observer with the distributed formation control and centroid tracking control law, we show that the formation shape can be maintained by utilizing its available relative measurements and the estimated relative measurements to its neighbors, and the group's centroid follows a desired trajectory. We present L2$$ {L}^2 $$ stability analysis of the closed‐loop system. Finally, we validate the proposed methods in a simulation result where a group of mobile robots can maintain a robust formation and maneuver in an unknown dynamic environment. [ABSTRACT FROM AUTHOR]

A negative ionospheric storm occurred over the North American sector on 4 November 2021. By the integration of hemispheric power (HP), Ionospheric Connection Explorer (ICON), Global‐scale Observations of the Limb and Disk and global navigation satellite system total electron content (TEC) observations, a complete observation chain is obtained for the first time. At 07:11 UT, prominent energy was input into high latitudes. From 11:51 to 15:49 UT, strong southwestward neutral wind was observed by ICON over the south of North America, followed by significant ∑O/N2 depletion (60%) and temperature enhancement (∼300 K at ∼150 km). TEC depletion started at 12:00 UT in the northeastern North America and expanded to most of the United States. The TEC reduction showed the latitudinally tilted structure similar to that of ∑O/N2 depletion and temperature enhancement, which was shaped by the southwestward neutral wind. The thermosphere‐ionosphere‐electrodynamics general circulation model (TIEGCM) reproduced the observations qualitatively and was utilized to investigate the details of the negative storm generation and evolution processes. Strong equatorward wind and ∑O/N2 depletion reached the North America at midnight, much earlier than the TEC depletion, which began at sunrise. At 90°W, the time delay between TEC and ∑O/N2 depletions increased from ∼3.3 hr at 30°N to ∼11 hr at 60°N. Several factors contributed to the time delay including the time difference between midnight and sunrise, ∑O/N2 transport direction, westward wind and the variation of solar elevation angle with latitude. Plain Language Summary: During geomagnetic storms, the increase/decrease of ionospheric plasma density during geomagnetic storms relative to geomagnetic calm period is called positive/negative ionospheric storms. Due to the lack of observations of thermospheric properties, there are very few studies on negative storms over middle latitudes using direct neutral wind and temperature observations. This paper investigates the negative storm over the North American sector on 4 November 2021. A complete observation chain of the negative storm generating processes is presented by using hemispherical power index, neutral wind, neutral temperature and composition, and total electron content (TEC) measurements. Strong southward and westward neutral wind were observed by Ionospheric Connection Explorer satellite over middle and low latitudes. Global‐scale Observations of the Limb and Disk satellite also recorded prominent thermospheric composition changes and temperature enhancement. Subsequently, TEC depletion occurred was consistent with that of neutral temperature and composition variations. A numerical model is employed to uncover the details of the processes. Thermospheric composition changes occurred between 40° and 60°N firstly at 06:00 UT in the North America sector while TEC depletion appeared at 12:00 UT. There were four factors contributed to the time lag between TEC and composition changes including the time difference between midnight and sunrise, composition transport, westward wind and solar elevation angle. Key Points: During a negative storm, strong southwestward neutral winds and prominent ∑O/N2 depletion were observed by Ionospheric Connection Explorer and Global‐scale Observations of the Limb and Disk, respectivelyA complete observation chain of the negative ionospheric storm generation at middle latitudes is first established for the first timeThe time delay between TEC and ∑O/N2 depletions increased from 3.3 hr at 30°N to ∼11 hr at 60°N [ABSTRACT FROM AUTHOR]

Smart‐phones have become a necessity for users due to their abundance of services such as global positioning system, Wi‐Fi, voice/video calls, SMS, camera, and so forth. It contains personal information of users including photos, documents, messages, and videos. Android‐based smart‐phones enriched with many applications (commonly known as apps) fascinates users to use this ubiquitous technology up to a full extent. With open architecture and 73% of market share, Android is the most popular mobile operating system (OS) among developers. At the same time, the increasing popularity of Android OS woos attackers or cyber‐criminals to exploit its vulnerabilities. The attackers write malicious code to harm the device and grab users' sensitive information. For example, ransomware (a form of malware) demands ransom from victims to liberate the ceased material for illegal financial gain. The existing survey papers cover the analysis and detection of generic Android malware. The focus of this survey paper is to present an in‐depth threat scenario of Android ransomware. This article not only provides a comprehensive survey on analysis and detection methods for Android ransomware since its beginning (2015) till date (2020); but also presents observations and suggestions for researchers and practitioners to carry out further research. [ABSTRACT FROM AUTHOR]

The ionosphere contains many small‐scale electron density variations that are under represented in smooth physics‐based or climatological models. This can negatively impact the results of Observation System Simulation Experiments, which use a truth model to simulate data. This paper addresses this problem by using ionosonde data to study ionospheric variability and build a new truth model with empirically driven variations. The variations are studied for their amplitude, horizontal and vertical size, and temporal extent. Results are presented for different local times, seasons, and at solar minimum and solar maximum. We find that these departures from a smooth background are often as large as 25% and are most prevalent near 250 km in altitude. They have horizontal spatial extents that vary from a few hundred to a few thousand kilometers, and typically have the largest horizontal extent at high altitudes. Their vertical extents follow the same pattern of being larger at high altitudes, but they only vary from 10s of km up to 200 km in vertical size. Temporally, these variations can last for a few hours. A procedure for using these spatial and temporal distributions to add empirically driven variance to a smooth truth model is outlined. This process is used to make a truth model with representative variations, which is compared to ionosonde data as well as Global Positioning System Total Electron Content data that was not used to inform the model. The new model resembles the data much better than the smooth models traditionally used. Plain Language Summary: The ionosphere is a region of space between 100 and 1,000 km in altitude. It contains many small variations in electron density that are not well‐described in typical models used in Observation System Simulation Experiments. This paper uses ionosonde data to study the size and duration of these variabilities, and then develops a method to add them to one of these typical models. The new model with the variabilities added more closely replicates real ionospheric measurements. Key Points: The amplitude and spatio‐temporal extent of ionospheric variabilities are quantified across altitude, local time, season, and solar cycleA method to add these variations into a smooth model is demonstrated and replicates ionospheric data wellThis noisy truth model enables more accurate Observation System Simulation Experiments [ABSTRACT FROM AUTHOR]

The impacts of ionospheric irregularities on precise point positioning (PPP) have been commonly noticed in the field of the ionosphere and the precise application of the Global Navigation Satellite System. But few attentions have been paid to how ionospheric irregularities deteriorate the performance of PPP. Aiming at exploring the mechanism of degradation of PPP solutions during the period of ionospheric irregularities, this paper investigates the impacts of ionospheric irregularities on the performance of kinematic PPP. The experiment uses GPS observation data sampled at the 30‐s interval over China on the days of 2014, 2015, and 2017 covering some active space weather, for example, solar and geomagnetic activities. The results show that the ionospheric irregularities caused increased positioning errors (decimeter‐ to meter‐level), enlarged phase residuals (decimeter‐level), and increased the number of detected cycle slips in PPP processing in low latitude regions of China. By proposing a novel strategy that compares the number of detected cycle slips from 30 s‐sampling interval data and 1s‐sampling interval data at the same station in an "aligned" mode, we present direct evidence of the existence of the falsely detected cycle slips in 30 s‐sampling interval data by the traditional cycle‐slip detection threshold in PPP processing. We reveal that the unnecessary and frequent reinitialization of ambiguity induced by the falsely detected cycle slips is dominantly responsible for the degradation of kinematic PPP solutions during the period of ionospheric irregularities. Our findings pointed out the direction for the improvement of kinematic PPP performance in the environment of ionospheric irregularities. Plain Language Summary: Ionospheric irregularities are electron density irregularities within the ionosphere. Ionospheric irregularity is the main concern in the field of Global Navigation Satellite System (GNSS) due to its impacts on the precise application of GNSS. This paper investigates the impacts of ionospheric irregularities on precise point positioning (PPP) in the region of China. The results indicate that ionospheric irregularities caused decimeter‐level and meter‐level degradation of kinematic PPP in the low‐latitude region of China. Meanwhile, we reveal the mechanism of degradation of kinematic PPP induced by ionospheric irregularities. The falsely detected cycle slips induced by ionospheric irregularities are the dominant reason that causes degradation of kinematic PPP during the period of ionospheric irregularities. Our findings advanced the understanding of the mechanism of the impacts of ionospheric irregularities on kinematic PPP performance. Key Points: Kinematic precise point positioning (PPP) performances in the multi‐event condition of ionospheric irregularities over China are evaluatedThe ionospheric irregularities caused increased cycle slips and degraded PPP solutions in the south of China from sunset to midnightExtensive misjudged cycle slips are dominantly responsible for the degradation of PPP solution during the period of irregularities [ABSTRACT FROM AUTHOR]

This paper will explore how mobile‐based GPS methods can advance insights into young itinerant vendors' informal livelihood mobilities. It examines the practicalities of using a GPS‐based method in a Majority World context whilst also discussing the merits of combining this approach with mobile methods. The ethical issues of using GPS technology 'on the move', and the impact that my presence had whilst I accompanied participants, is also discussed. [ABSTRACT FROM AUTHOR]

In this study, we used observations from multiple instruments (all‐sky imager [ASI], digisonde, and Beidou geostationary satellite global positioning system receivers) to show the occurrence and evolution of two plasma density enhancement structures (PDESs) during the night of 8 February and 4 November 2018. The PDESs were elongated from northwest to southeast. Their zonal scales were about 200–400 km and longitudinal ranges were about 800–1,400 km. Within the PDES, the plasma density can be enhanced by about two times over the background density. The PDESs appeared before midnight and gradually dissipated after midnight. Plasma density depletion structures appeared within the PDES at the later stage of PDES. Each PDES event lasted for over 4 hours. The morphology and evolution of the PDESs presented in this paper are different from those reported in previous studies. In addition, based on the thermosphere‐ionosphere‐electrodynamics general circulation model simulations and digisonde observations, we proposed a possible cause for the PDESs in the events, in which the occurrence and evolution of PDES are related to the variations of thermospheric meridional winds in the equatorial region. Plain Language Summary: Ionospheric plasma irregularities or disturbances are frequently observed in the equatorial region and have been the focus of ionospheric research. These irregularities include plasma bubbles, traveling ionospheric disturbances, and plasma density enhancements. They have a great impact on the trans‐ionospheric radio wave signals. Most of the previous studies show that the plasma density enhancements occur over large scales and the occurrence of plasma density enhancements is usually accompanied by plasma density depletions in the adjacent areas, and hence, the formation of the density enhancement is suggested to be related to the plasma density depletion. In this study, two unique plasma density enhancement structures (PDESs) were observed using multiple instruments. The observed plasma density enhancements were elongated from northwest to southeast, which is different from previous studies. This paper presents the full evolution of the plasma density enhancement from its appearance to disappearance. In addition, we proposed a possible formation process for the equatorial plasma density enhancement in which the occurrence and evolution of PDES are related to the variations of thermospheric meridional winds in the equatorial region. Our results provide new insight into the dynamics and variability of the coupled thermosphere and ionosphere system in the equatorial region. Key Points: Evolution of equatorial ionospheric plasma density enhancements from occurrence to disappearance was illustrated with multiple data setsThe plasma density enhancement structures (PDESs) were elongated from northwest to southeast, with their sizes changing with time, and they produced Spread F in ionogramsVariations in neutral winds may contribute to the occurrence of the observed PDES [ABSTRACT FROM AUTHOR]

Recent advances in the accessibility and reliability of mobile technologies, roaming services and associated data have led to an increased use of modern navigational devices using Global Navigation Satellite Systems (GNSS). This paper reports on a study that explored concerns about over‐reliance on these navigational technologies, specifically among young people in the Global North. Based on an experiment in which participants were asked to navigate a series of different (unfamiliar) routes on foot, using different navigational technologies each time, we argue that routes navigated are more memorable, and the process of way‐finding is more enjoyable, when navigational tools/methods enable sensory and social interactions. GNSS aids, although claimed by participants as their preferred navigational aid, were the least enabling in this regard. We conclude that, although concerns about young people's way‐finding abilities may be overstated, the importance of sensory and social interactions with(in) environments might usefully be borne in mind in the development of future GNSS aids and locative media. [ABSTRACT FROM AUTHOR]

Currently, studies on autonomous driving are being actively conducted. Vehicle positioning techniques are very important in the autonomous driving area. Currently, the global positioning system (GPS) is the most widely used technology for vehicle positioning. Although technologies such as the inertial navigation system and vision are used in combination with GPS to enhance precision, there is a limitation in measuring the lane and position in shaded areas of GPS, like tunnels. To solve such problems, this paper presents the use of LED lighting for position estimation in GPS shadow areas. This paper presents simulations in the environment of three‐lane tunnels with LEDs of different color temperatures, and the results show that position estimation is possible by the analyzing chromaticity of LED lights. To improve the precision of positioning, a fuzzy logic system is added to the location function in the literature [1]. The experimental results showed that the average error was 0.0619 cm, and verify that the performance of developed position estimation system is viable compared with previous works. [ABSTRACT FROM AUTHOR]

The 2015 Mw 7.8 Gorkha (Nepal) earthquake induced prolonged postseismic deformation extending northward beyond the Yarlung Zangbo Suture, which provides unique opportunities to better understand the lithospheric rheology in Himalaya and southern Tibet. Here, we used the first 5‐year Global Positioning System observations to study the main postseismic processes following this event, including viscoelastic relaxation and afterslip, based on a three‐dimensional finite element model. We considered a realistic geometry of the underthrusting Indian plate according to various geophysical images. We found that the models with a uniform elastic Indian lower crust fail to fit the vertical displacements. A heterogeneous Indian lower crust with the transition from elastic (high‐viscosity) to low‐viscosity approximately under the Main Central Thrust is required to reproduce the observed postseismic uplift between China‐Nepal border and Peiku Lake, indicating the weakness of the Indian lower crust from the Lesser to High Himalaya. The afterslip simulated using a weak shear zone takes place in the adjacent area downdip of the rupture zone. The preferred model suggested that viscosities of the Tibetan lower crust, weakened Indian lower crust, and shear zone are 3 × 1018, 1019, and 4 × 1018 Pa s, respectively. The viscosity of the underthrusting Indian upper mantle was roughly estimated to be greater than 1021 Pa s. The model results imply that the near‐field deformation is dominated by both afterslip and viscoelastic relaxation of the weakened Indian lower crust, not only afterslip as suggested by previous studies. Plain Language Summary: On 25 April 2015, an Mw 7.8 earthquake occurred in the central Himalayan area (near Gorkha). Global Positioning System (GPS) measurements show that the induced postseismic deformation extends northward beyond the Yarlung Zangbo Suture. In this paper, we considered the postseismic displacements within 5 years after this earthquake and studied the two main postseismic processes (afterslip and viscoelastic relaxation of the lower crust and upper mantle) using finite element modeling. We explored the parameters governing afterslip and viscoelastic relaxation of the lower crust and upper mantle beneath Himalaya aiming to fit GPS observations. We found that an Indian lower crust with the transition from elastic to low‐viscosity approximately under the Main Central Thrust is necessary to explain the observed uplift between China‐Nepal border and Peiku Lake. The postseismic deformation of the 2015 Gorkha earthquake provides independent evidence for the weakness of the Indian lower crust from Lesser to High Himalaya, which is of great importance to understand the uplift evolution of the Himalaya and Tibetan Plateau. Key Points: We study the postseismic viscoelastic relaxation and afterslip due to the 2015 Mw 7.8 Gorkha earthquake by finite element modelingA heterogeneous Indian lower crust is required to reproduce the observed postseismic uplift between China‐Nepal border and Peiku LakeThe modeling results reveal the weakness of the Indian lower crust from the Lesser to High Himalaya [ABSTRACT FROM AUTHOR]

Ionospheric responses to geomagnetic storms can cause irregular plasma structures and scintillation of Global Navigation Satellite System (GNSS) signals. In this paper, we investigate time lags between the detection of GNSS signal scintillation at northern hemisphere auroral latitudes and the onset of 15 geomagnetic storms that occurred in 2015–2017. The results show that the time lags between the detection of ground‐based GNSS scintillations and the observed sudden change in solar wind parameters are between tens of minutes and 15 hr. This time lag consists of two segments. The first segment is about 30–80 min, which is the lag between observed disturbances in the geomagnetic field and solar wind disturbances detected by orbiting spacecrafts around the L1 point. The second segment is between the observed GNSS signal scintillation and the storm sudden commencement (SSC). This second lag segment varies in the range of about 10–830 min and highly depends on the storm onset time and geomagnetic locations of GNSS signal propagation paths. Longer time lags over 450 min were observed with the signal ionospheric piercing point at 60–70° geomagnetic latitudes (MLAT) on the dayside, while shorter lags of 10∼450 min were observed with the signal IPPs at 68–81° MLAT and on the nightside at the time of SSC. The lag time variations can be explained by ionospheric irregularity production and transport processes associated with a variety of auroral and polar cap phenomena in response to solar wind coupling to the magnetosphere and ionosphere. Key Points: Time lags between storm sudden commencement and scintillation detections by ground‐based Global Navigation Satellite System receivers at northern auroral latitudes were surveyedThe time lags varied with geomagnetic latitude and magnetic local time of satellite‐receiver line‐of‐sight signal paths assumed at ionospheric piercing pointsShorter time lag was detected by the observations close to aurora cusp as well as those on the nightside at the storm onset [ABSTRACT FROM AUTHOR]

Using new continuous geodetic time series, we identify five shallow slow slip events (SSEs) offshore and beneath the Osa peninsula in southern Costa Rica. An early event was detected by one station in 2013, and two events occurring in close succession in both 2018 and 2022 were detected by multiple stations, indicating a preliminary recurrence interval of ∼4–5 years. While SSEs have been observed to the northwest at Nicoya, this is their first documentation in southern Costa Rica. Modeled slip distributions of the 2018 and 2022 events indicate they likely ruptured the same or overlapping patches of the plate interface, near the trench, updip of the 1983 Mw 7.4 Osa event. Immediately offshore, estimated cumulative slip from the 2018 and 2022 events is sufficient to close the slip deficit from tectonic loading over the recurrence interval, potentially limiting the magnitude and spatial slip distribution of future large ruptures. Plain Language Summary: Slow slip events (SSEs), effectively slow earthquake ruptures, are a phenomena that have been observed in many subduction zones around the world. While SSEs in subduction zones are often observed at depth, this is likely due to our observational capability being better when the events occur under land. By contrast, shallow events are more difficult to observe because they often occur under the ocean, despite their potential relationship to large, damaging, and/or tsunamigenic earthquakes. In this paper, we present research that identifies shallow slow slip events in a location where they have not been previously observed, the Osa Peninsula in southern Costa Rica. In total we observe five shallow SSEs, sometimes occurring in pairs, that appear to rupture every ∼4–5 years. Additionally we suggest that the amount of slip in these events may be sufficient to account for all the tectonic convergence in some locations, potentially limiting the size of future large earthquakes. Key Points: We identify five slow slip events in southern Costa Rica, one in 2013, and two events occurring in close succession in both 2018 and 2022The recent four events likely ruptured the same shallow patch of the megathrust, extremely close to the Middle American TrenchEvents in 2018 and 2022 seem to release nearly all slip accumulated by plate motion over a ∼4 year recurrence interval in some locations [ABSTRACT FROM AUTHOR]

In this paper, a new approach to visual geo‐localization for natural environments is proposed. The digital elevation model (DEM) data in virtual space is rendered and construct a panoramic skyline database is constructed. By combining the skyline database with real‐world image data (used as the "queries" to be localized), visual geo‐localization is treated as a cross‐modal image retrieval problem for panoramic skyline images, creating a unique new visual geo‐localization benchmark for the natural environment. Specifically, the semantic segmentation model named LineNet is proposed, for skyline extractions from query images, which has proven to be robust to a variety of complex natural environments. On the aforementioned benchmarks, the fully automatic method is elaborated for large‐scale cross‐modal localization using panoramic skyline images. Finally, the compound index is delicately designed to reduce the storage space of the positioning global descriptors and improve the retrieval efficiency. Moreover, the proposed method is proven to outperform most state‐of‐the‐art methods. [ABSTRACT FROM AUTHOR]

The entire global operation of the newly launched BDS global navigation satellite system (BDS‐3) was completed in July 2020. After that, a series of performance tests were conducted, such as positioning, navigation, and signal experiments. However, the precipitable water vapor (PWV) retrieval performance evaluation of BDS‐3 has not yet been carried out, so in this paper, we thoroughly verified its accuracy with AIRS v7, ERA5, and radiosonde data to know the current performance of BDS‐3 PWV. From the tests applied with different satellite systems, we found that BDS‐3 has a comparable PWV retrieval performance as global positioning system (GPS), and a better outcome was achieved using the combined data from GPS and BDS‐3. Furthermore, BDS‐3 PWV accuracy calibrated by AIRS v7 showed a strong correlation with the spatial distribution. In addition, the PWV content decreased with the climbing of the latitude and elevation, and the relative root mean square error (ReRMSE) indicated better in the low‐latitude areas. Finally, the effect of different surface types on PWV performance was analyzed, showing the BDS‐3 PWV accuracy in the land type was the highest, the sea one was the lowest, and the coast type was in the middle. These findings will provide a good reference for the community to understand the PWV performance of BDS‐3 at the present stage. Plain Language Summary: Water vapor content is a basic condition for precipitation formation and a major atmospheric radiation‐absorbing gas. Therefore, precipitable water vapor (PWV) is one of the most important parameters in weather prediction, the global hydrological cycle, climate change, and other environmental issues. BDS global navigation satellite system (BDS‐3) has provided the global navigation service since 31 July 2020. Like global positioning system (GPS), BDS‐3 can be utilized as an alternative system to retrieve PWV. However, the PWV retrieval performance of BDS‐3 has not yet been made. Thus, here we apply the data from AIRS v7, ERA5, and radiosonde to evaluate the accuracy of BDS‐3 PWV. From the results, we know that the current PWV retrieval performance of BDS‐3 is comparable to GPS. Furthermore, BDS‐3 PWV accuracy is related to the station location. Root mean square error (RMSE) is better at high latitudes, while relative RMSE is the opposite. Finally, we find that surface types influence PWV performance, showing the highest accuracy on the land, the middle on the coast, and the lowest on the sea. The above analyses are conducive to a deeper understanding of the BDS‐3 PWV performance. Key Points: The precipitable water vapor (PWV) retrieval performance of the newly launched BDS global navigation satellite system (BDS‐3) is first madeThe current PWV retrieval performance of BDS‐3 is comparable to global positioning systemBDS‐3 PWV accuracy validated with Atmospheric Infrared Sounder v7 data is related to the station location and the surface types [ABSTRACT FROM AUTHOR]

Transionospheric satellite signals are exposed to perturbation, caused by irregularities generated in the ionosphere. However, the characteristics of the satellite motion can have an additional impact on signal perturbation, in addition to the effects of irregularity structures, that drift from west to east during geomagnetic quiet conditions. This paper reports the effect of Global Positioning System satellite geometry, on tracking loop performance of ground‐based receivers, during occurrence of ionospheric scintillations. Observations are made from station Calcutta (22.58°N, 88.38°E geographic; magnetic dip 34.54°), located near the northern crest of Equatorial Ionization Anomaly, during three different solar activity periods (March 2014, March 2015, and March 2022). Efforts have been made to study the correlation of east‐west component of satellite velocity at Ionospheric Pierce Point (IPP) with duration of loss‐of‐lock and rate of signal fading (<−10 dB), from ground scintillation pattern observations. Results of this study show 75%–78% correlation between duration of loss‐of‐lock and eastward component of satellite velocity, for all three period of observation. Subsequently, shorter duration of loss‐of‐lock has been observed corresponding to satellite velocity being westward. Signal fading rate is found to decrease with increasing satellite velocity, having median value of the fading rate cumulative distribution percentage, corresponding to satellite velocity of 16.69, 31.76, and 19.14 m/s respectively during March 2014, March 2015, and March 2022. Results of this study also indicate direction and component of satellite velocity at IPP to be a dominant cause of signal outage, even during periods of weak to moderate scintillations. Plain Language Summary: Equatorial ionosphere is often characterized with generation of irregularities which are electron density depleted regions in the nighttime F layer, that drift from west to east with an average velocity of 100 m/s. Transionospheric satellite links, when intersected by these irregularities can cause fluctuation in signal amplitude and phase, received on ground. Such fluctuations, commonly known as scintillations, are observed as a regular phenomenon over low‐latitude and equatorial stations, especially during equinoctial period of a high solar activity year. The station Calcutta, being located near the northern crest of Equatorial Ionization Anomaly, witnesses some of the worst cases of signal perturbation due to effect of the medium, sometimes leading to complete outage of signal, termed as loss‐of‐lock. However, occurrence of such events can have contribution from both the motion of irregularities and satellites. Under condition of synchronization of signal motion with irregularity drift, tracking loop of a receiver can result in longer duration of loss‐of‐lock. In this study, efforts have been made to understand the effect of Global Positioning System satellite geometry on such tracking loop performance of ground‐based receivers, in presence of scintillation. Results of this study indicate higher duration of loss‐of‐lock when eastward component of satellite velocity is higher. Key Points: Effect of Global Positioning System satellite geometry on tracking loop performance of ground‐based receivers in presence of scintillationStudy of east‐west component of satellite velocity at Ionospheric Pierce Point and its correlation with occurrence of loss‐of‐lockObservation of signal fading rate, having depth <−10 dB, to study its correlation with synchronization of irregularity structure [ABSTRACT FROM AUTHOR]

Machine learning (ML) has been increasingly applied to space weather and ionosphere problems in recent years, with the goal of improving modeling and forecasting capabilities through a data‐driven modeling approach of nonlinear relationships. However, little work has been done to quantify the uncertainty of the results, lacking an indication of how confident and reliable the results of an ML system are. In this paper, we implement and analyze several uncertainty quantification approaches for an ML‐based model to forecast Vertical Total Electron Content (VTEC) 1‐day ahead and corresponding uncertainties with 95% confidence intervals (CI): (a) Super‐Ensemble of ML‐based VTEC models (SE), (b) Gradient Tree Boosting with quantile loss function (Quantile Gradient Boosting, QGB), (c) Bayesian neural network (BNN), and (d) BNN including data uncertainty (BNN + D). Techniques that consider only model parameter uncertainties (a and c) predict narrow CI and over‐optimistic results, whereas accounting for both model parameter and data uncertainties with the BNN + D approach leads to a wider CI and the most realistic uncertainties quantification of VTEC forecast. However, the BNN + D approach suffers from a high computational burden, while the QGB approach is the most computationally efficient solution with slightly less realistic uncertainties. The QGB CI are determined to a large extent from space weather indices, as revealed by the feature analysis. They exhibit variations related to daytime/nightime, solar irradiance, geomagnetic activity, and post‐sunset low‐latitude ionosphere enhancement. Plain Language Summary: Space weather describes the varying conditions in the space environment between the Sun and Earth that can affect satellites and technologies on Earth, such as navigation systems, power grids, radio, and satellite communications. The manifestation of space weather in the ionosphere can be characterized using the Vertical Total Electron Content (VTEC) derived from Global Navigation Satellite Systems observations. In this study, the machine learning (ML) approach is applied to approximate the nonlinear relationships of Sun‐Earth processes using data on solar activity, solar wind, magnetic field, and VTEC. However, the measurements and the modeling approaches are subject to errors, increasing the uncertainty of the results when forecasting future instances. For reliable forecasting, it is necessary to quantify the uncertainties. Quantifying the uncertainty is also helpful for understanding the ML‐based model and the problem of VTEC and space weather forecasting. Therefore, in this study, ML‐based models are developed to forecast VTEC within the ionosphere, including the manifestation of space weather, while the degree of reliability is quantified with a target value of 95% confidence. Key Points: Machine learning‐based Vertical Total Electron Content models with 95% confidence intervals (CI) are developed for the first time using four approaches to quantify uncertaintiesBayesian Neural Network quantifying model and data uncertainties contains ground truth within CIs, but is computationally intensiveQuantile Gradient Boosting is fastest with comparable performance in terms of uncertainty; CIs largely determined from space weather indices [ABSTRACT FROM AUTHOR]

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