Global Positioning System Stations Research Articles

Standard PSInSAR approach: Experimental study on the sensitivity of different bounds change on the deformation

Abstract. An experimental study conducted on standard PSInSAR technique to check the sensitivity of different bounds on the deformation results. This study is motivated by the results obtained from employment of different parameter ranges, with the assumption of the linear behavior of the deformation. despite implementation of slight parameter change shows similarity in most of the PS points. However, significant PS points display slightly different deformation measurements and trends. This change in the PS points motivated an experimental study to evaluate, analyze and assess the results from each different bounds through searching the solution space to find the best fitting to the estimated model, besides assessing of the temporal coherence estimator as quality and fitting indicator. A high-resolution TerraSAR-X (TSX) dataset is used to estimate the deformation using linear model and check the behavior over time. These dataset cover Wuhan city as a case study within two years to avoid non-linearity in the deformation. The main part of this experiment is the descriptive of the statistics across all trials of different bounds. Then, assessing the measurement results of the trials, and the coherence estimator that used as a quality indicator to assess the quality of the PS points in comparison with the standard deviation. The results of the measurements indicate that while the coherence estimator select the PS points based on their stability and fitting to estimated model but does not provide a big difference as function of different bounds through searching the solution space. The results are confirmed with the available global Positioning system (GPS) station in our study area and displays similar trends and patterns over all the trials with slight differences with the different parameters range. The statistical analysis and assessment reveals differences in the velocity results and erroneous during changing the parameters range.

Analysis of total electron content over the African low-latitude region during the maximum phase of solar cycle 24 (2012–2014)

This study examined the ionospheric variation over the African low-latitude region using Total Electron Content (TEC) and its wavelet power spectrum (WPS). TEC data were obtained from five Global Positioning System (GPS) stations located in the trough and crests of the equatorial ionization anomaly (EIA) in both hemispheres during quiet periods of the maximum phase of solar cycle 24 (2012–2014). Our results revealed a striking equinoctial asymmetry (EA) with stronger TEC and higher solar flux in September equinox than March equinox of 2012–2013, with the reverse being the case in 2014. As such, the difference in solar flux between both equinoxes might have played a dominant role in driving the EA. Furthermore, we found a hemispheric asymmetry in TEC with higher value towards the crest in the northern hemisphere (southern hemisphere) in September equinox (March equinox) of 2012–2013. In 2014, nevertheless, TEC was remarkably higher towards the crest located in the southern hemisphere in September equinox only. The chaotic time series methods used to examine the TEC variations showed positive Lyapunov exponents (LE) at all stations. This indicated the presence of chaoticity in the African EIA. Nevertheless, stations located towards the southern crest (Eldoret and Dodoma) had the maximum LE values while those at the magnetic equator (Adis Ababa) and northern crest (Nama and Al Wajh) had the minimum values. Consequently, the changes in the internal dynamics of the equatorial ionosphere have impacts on its chaotic behavior.

GPS displacement dataset for the study of elastic surface mass variations

Abstract. Quantification of uncertainty in surface mass change signals derived from Global Positioning System (GPS) measurements poses challenges, especially when dealing with large datasets with continental or global coverage. We present a new GPS station displacement dataset that reflects surface mass load signals and their uncertainties. We assess the structure and quantify the uncertainty of vertical land displacement derived from 3045 GPS stations distributed across the continental US. Monthly means of daily positions are available for 15 years. We list the required corrections to isolate surface mass signals in GPS estimates and screen the data using GRACE(-FO) as external validation. Evaluation of GPS time series is a critical step, which identifies (a) corrections that were missed, (b) sites that contain non-elastic signals (e.g., close to aquifers), and (c) sites affected by background modeling errors (e.g., errors in the glacial isostatic model). Finally, we quantify uncertainty of GPS vertical displacement estimates through stochastic modeling and quantification of spatially correlated errors. Our aim is to assign weights to GPS estimates of vertical displacements, which will be used in a joint solution with GRACE(-FO). We prescribe white, colored, and spatially correlated noise. To quantify spatially correlated noise, we build on the common mode imaging approach by adding a geophysical constraint (i.e., surface hydrology) to derive an error estimate for the surface mass signal. We study the uncertainty of the GPS displacement time series and find an average noise level between 2 and 3 mm when white noise, flicker noise, and the root mean square (rms) of residuals about a seasonality and trend fit are used to describe uncertainty. Prescribing random walk noise increases the error level such that half of the stations have noise > 4 mm, which is systematic with the noise level derived through modeling of spatially correlated noise. The new dataset is available at https://doi.org/10.5281/zenodo.8184285 (Peidou et al., 2023) and is suitable for use in a future joint solution with GRACE(-FO)-like observations.

Prediction of ionospheric total electron content over low latitude region: Case study in Ethiopia

This study mainly focuses on the prediction of the variability of the Total Electron Content (TEC) affecting space and ground-based technological infrastructures vulnerable to extreme space weather events. The impact of solar wind conditions (SWC) can be quantified by measuring the ionosphere’s TEC. We used a machine learning (ML) algorithm based on the Support Vector Machine (SVM), Long Short-Term Memory (LSTM) Neural Network (NN), and International Reference Ionosphere 2016 (IRI 2016) models to predict the hourly TEC over Ethiopia during quiet and storm geomagnetic conditions. We considered TEC data from the Global Positioning System (GPS) stations at ADIS, CURG, and NEGE during the years 2013 to 2016. The results indicated that the SVM model predicted the hourly TEC variation with a root mean square error (RMSE) between 2.136 and 7.923 Total Electron Content Unit (TECU) under different ionospheric conditions. For the LSTM model, the RMSE between the predicted and observed TEC lies between 1.483 and 2.527 TECU. But the empirical IRI 2016 models’ RMSE from GPS TEC is in the range of 4.777 and 14.519 TECU. The statistical study points out the LSTM has the highest prediction accuracy and is the most robust for accurate prediction of ionospheric TEC in comparison to the SVM and IRI 2016 models throughout both storm and quiet periods. The result can be further improved with a lower RMSE (high correlation) by utilizing auxiliary data and increasing the number of stations employed in the study. This research adds fresh insights to deep learning applications in space weather forecasting in the region of interest.

Analysis of GPS TEC anomalies associated with Mw > 7 earthquakes in Japan

The Global Positioning System (GPS) provides insights into the Earthquakes (EQs) ionospheric anomalies. Different space-and-ground parameters are used to observe EQ precursors. This paper uses the Total Electron Content (TEC) from nearby operating GPS stations to detect perturbation in the ionosphere before and after four EQs in Japan in 2011. In addition, the TEC variations in relation to the depth and magnitude of the EQs are noticed. The analysis shows significant variations in TEC to depth and magnitude in association with each main shock. TEC value abruption starts on 8 March and continues for 6 days in March. In April, TEC abnormalities start 5 days before and after the man shock. The geomagnetic Kp index is higher than four from March 10 to 12. The anomalies in this study are clearly associated with geomagnetic storms, as the Kp index is active. Moreover, the Dst index is below the negative 50 (nT) in the seismic period of March and April. The ionosphere parameters will define the severity of seismic activity in future.

Groundwater Storage Variations in the Main Karoo Aquifer Estimated Using GRACE and GPS

The Gravity Recovery and Climate Experiment (GRACE) provided valuable insights into variations in Groundwater Storage (GWS). However, the sensitivity of utilizing Global Positioning System (GPS) time series displacement data for detecting changes in GWS remains a subject of ongoing discussion. In order to estimate the spatiotemporal GWS, we selected a vertical displacement from 65 GPS stations located in the Main Karoo Aquifer (MKA). We performed total water storage (TWS) inversion on GPS vertical displacement components; after that, we deducted surface water components based on the Global Land Data Assimilation System (GLDAS) from January 2013 to December 2021. Additionally, for validation, we compared our GWS estimates with the GRACE-derived GWS and observed GWS values derived from the WaterGAP Global Hydrology Model (WGHM) compartments. We discovered that the TWS and GWS trends derived from GPS and GRACE exhibited similar behaviors with trend values overestimated by GRACE and WGHM. Our findings demonstrate relatively typical behavior between GPS and GRACE in the first and second principal component behaviors (PCs) and empirical orthogonal function (EOF) loadings (or spatial patterns). With a contribution of 71.83% to GPS-derived GWS variability and 68.92% to GRACE-derived GWS variability, EOF-1 is a relatively potent factor. For Principal Components PC1 and PC2, the GRACE and GPS PCs have correlation coefficients of 0.75 and 0.84, respectively. Finally, with higher temporal resolution, GPS can perform the same task as GRACE in hydrological applications. In addition, GPS can add important and valuable information to assess regional GWS change.

Undifferenced precise time transfer with information‐constraints

AbstractSatellite navigation systems enable long‐distance and high‐precision time transfers. The authors proposed an undifferenced precise time transfer method with information constraints in this study. A more accurate receiver clock offset can be obtained by constraining the station coordinate parameters and receiver clock offset parameters to achieve a precise time transfer. In this example, the research object is the time transfer link established by the Global Positioning System observation station using a caesium clock, rubidium clock, and hydrogen clock. The clock difference sequence of the time‐transfer link was calculated by combining the observation data and precise products. Following analysis of the examples, the following conclusions were reached. The undifferenced precise time transfer method based on information constraints can effectively be used to smooth the clock difference sequence of the receiver and the clock difference sequence of the time transfer link. To some extent, this method can also be used to reflect the performance of atomic clocks at Global Positioning System stations and is better suited for the precise time transfer of the equal‐clock long‐baseline time transfer link. Simultaneously, the frequency stability of this method is improved significantly in the short term compared to the traditional scheme without any constraints. The improvement of frequency stability is helpful to improve the accuracy of time transfer.

Imaging the Sources of the March 2021 Seismic Sequence in Thessaly Basin (Central Greece) from Kinematic Slip Inversion and Backprojection of Waveform Envelopes

ABSTRACT In March 2021, a series of three moderate events with moment magnitudes Mw 6.3, 6.0, and 5.5 occurred within a span of 10 days in northern Thessaly, Greece, resulting in a stop–start pattern. The moment tensors (MTs) obtained from the events suggested normal faulting along distinct yet adjacent southeast–northwest-trending faults, indicating a sequential triggering process. We applied two methods to investigate the spatial and temporal characteristics of the source process of the triplet. This approach includes linear slip inversion of regional seismic waveforms and static Global Positioning System offsets, along with backprojection of regional waveforms using the Source-Scanning Algorithm technique. The detailed modeling suggests that three adjacent, subparallel (∼300°), and low-angle, detachment-type structures were responsible for the earthquakes. The stress axes orientation was determined by inverting a dataset of recomputed MTs combined with published solutions of the sequence. The results indicated a clockwise rotation of the local extensional axis by ∼25° compared to the regional ∼north–south extension. This rotation is consistent with the orientation of the modeled seismogenic structures. Inversions for both nodal planes and grid-searching fault geometry and orientation showed that for the first-two strongest events, the activated fault planes dipped to the northeast, whereas an antithetic (southwest dipping) fault was activated during the last weaker event. For the Mw 6.3 event, both the independent analyses indicated an overall rupture duration of ∼10 s, energy bursts above and near the hypocenter, up-dip (toward the southwest) rupture propagation in the early stages of the source process, and a bilateral rupture at later stages.

Slow Slip Events Associated with Seismic Activity in the Hikurangi Subduction Zone, New Zealand, from 2019 to 2022

Slow slip events (SSEs) are geophysical phenomena primarily occurring in subduction zones. These events are often associated with seismic activity and can be detected by Global Positioning System (GPS). However, the relationship between SSEs and seismic activity remains unclear. To further investigate SSEs associated with seismic activity, we conducted SSE detection and inversion for the period from 2019 to 2022 on New Zealand’s North Island, where both SSEs and seismic activity frequently occur. By modeling daily GPS coordinate time series from 40 GPS stations and applying the Network Inversion Filter (NIF) method, we obtain surface displacements, cumulative slips, and slip rates for eight shallow SSEs. Subsequently, we conduct a statistical analysis of seismic activity concerning its spatial distribution and frequency before, during, and after SSE occurrences. The results indicate that SSE1 and SSE7 exhibited larger cumulative slips, at 14.35 and 7.20 cm, and surface displacements, at 4.97 and 2.53 cm, respectively. During their occurrences, the seismic frequency noticeably increased to 6.5 and 5.6 events per day in the Eastern Coastal Region (ECR) of New Zealand’s North Island. However, the other six SSEs, characterized by cumulative slips of less than 6 cm and maximum surface displacements of less than 2 cm, did not lead to a noticeable increase in seismic frequency during their occurrences in the ECR. In the Main Slip Regions (MSR) of these eight SSEs, a significant upward trend in seismic frequency was observed during their occurrences. Therefore, it can be inferred that in the ECR of New Zealand’s North Island, all SSEs result in an increased seismic frequency within their respective MSRs, but only significant SSEs impact the seismic frequency of the ECR. Monitoring shallow SSEs may contribute to the identification and recording of seismic activity.

Analysis of GPS-TEC and IRI model over equatorial and EIA stations during solar cycle 24

Total Electron Content (TEC) measurements provided by Global Positioning System (GPS) as well as the International Reference Ionosphere – 2016 model (IRI01-Corr, IRI-2001, and NeQuick) model were compared at two Indian GPS stations: equatorial station Bangalore (12.580N, 77.350 E) and equatorial ionization anomaly (EIA) station Lucknow (26.500N, 80.550 E) during the solar cycle 24 extending from 2007 to 2017. The spectral, regression and statistical analysis displays a double-hump shape with counterclockwise hysteresis within TEC. The solar flux along with the TEC showed erratic as well as sluggish trends throughout the increasing period and flat and rapid throughout the decreasing period of the solar cycle 24. The semiannual and winter anomaly is discovered to be a constant feature throughout the solar cycle. The main idea of the current study is to investigate the performance of IRI01-Corr, IRI-2001, and NeQuick TEC in contrast to GPS TEC data throughout solar cycle 24 at the Indian equatorial and EIA stations. The modeled TEC data exhibit almost complete agreement with the measurement highlighting the same trends in the solar cycle as well as semiannual and seasonal changes. However, there are clear biases between the observed and modeled TECs when local time, seasons, as well as solar activity phases are considered. The main findings of this paper are that the NeQuick model generally underestimates noon-time TEC while the IRI-2001 model overestimates the same. The error in estimating noontime TEC from the IRI model using IRI-2001 as a topside at the EIA station is higher (142 %) than that at the equatorial station (42 %).

Bi-LSTM based vertical total electron content prediction at low-latitude equatorial ionization anomaly region of South India

In this study, we consider Bi-directional Long Short Term Memory (Bi-LSTM) model based Vertical Total Electron Content (VTEC) prediction over Thanjavur (Geographic 10.72˚ N, 79.01˚ E, Geomagnetic 2.34˚ N, 152.19˚ E) Global Positioning System (GPS) station. This station is located at low latitude Equatorial Ionization Anomaly (EIA) region of 2˚ geomagnetic dip latitude and has unique ionospheric dynamics. In this region, the VTEC prediction is crucial and challenging for space weather and the Sixth Generation (6G) Internet of Space (IoS) application to support early warning systems and future spatial data transmissions. A Deep Learning (DL) model based on Bi-LSTM was developed and trained for F10.7 and Dst index for predicting the VTEC. This study highlights the prediction of VTEC for any day that includes solstice and equinox time frames. The Bi-LSTM has an improvement of 28 % in mean absolute error (MAE), 48% in mean square error (MSE) and 24% in root mean square error (RMSE) as compared to the conventional Long Short Term Memory (LSTM) network. Hence, this Bi-LSTM model can be helpful to predict the VTEC in the EIA region and may be helpful to extrapolate over the unmeasured grid region of ocean and land.

Peak Ground Velocity (PGV) estimation of Mw 5.6 Cianjur earthquake November 11, 2022 using Global Positioning System (GPS)

The primary purpose of GPS is to be used for positioning, navigation, and timing (PNT). In the last decade, research on GPS for earthquake hazards has increased rapidly, such as for tectonic deformation, GPS seismology, modeling earthquake source parameters, estimation of magnitude, etc. In this study, following the Mw 5.6 Cianjur earthquake on November 11, 2022, we estimate the peak ground velocity from the CJUR GPS station, which is located about 15 km from the epicenter. We compute GPS velocity from the high-rate GPS receiver independent exchange (RINEX) data and broadcast ephemeris. Using a narrow line combination of L1 and L2 observations, we invert velocity epoch by epoch. The result shows the CJUR GPS station has a peak ground velocity of about 11.5 cm/s and equal to VI MMI scale. The peak ground velocity from the GPS station could be important for deriving the earthquake shakemap. By increasing the number of GPS stations in Indonesia, it is very important to support earthquake hazard monitoring.

Variation of Total Electron Content over Nepal during Geomagnetic Storms: GPS Observations

Geomagnetic storms have very profound effects on the Total Electron Content (TEC) of the ionosphere. In order to investigate the equatorial and low-latitude ionospheric response to the geomagnetic storms of varying intensities, a detailed study of vertical TEC (VTEC) variations resulting from Global Positioning System (GPS) data acquired at four GPS stations in Nepal along 80°–90° E longitude and 26°–30° N latitude sector has been carried out in the present work. The results were analyzed with other favorable inducing factors (solar wind parameters and geomagnetic indices) affecting TEC to constrain the causative factor. Positive phases are observed for all the storms studied. During the severe geomagnetic activity, the deviation was ~18 TECU, while it was recorded ~12 TECU and ~8 TECU during moderate and minor geomagnetic activity, respectively. The Detrended Cross-Correlation Analysis (DXA) illustrates that the value of the hourly average VTEC of the BESI station was found to have a strong positive correlation with other stations in all types of storm events, indicating a similar response of all stations towards the space weather events. In addition, the correlation of VTEC with solar wind parameters and geomagnetic indices illustrated that the VTEC shows a strong positive association with solar wind velocity (Vsw) in all three geomagnetic events. In contrast, the correlation of plasma density (Nsw), interplanetary magnetic field (IMF-Bz), the symmetric horizontal component of geomagnetic field (SYM-H), and Geomagnetic Auroral Electrojet (AE) index with VTEC vary with the intensity of the storm. Overall results of the study have revealed the characteristic features of TEC variation over Nepal regions during magnetic storms, which validates earlier research on ionospheric responses to geomagnetic storms and theoretical assumptions.

DCB estimation and analysis using the single receiver GPS/GLONASS observations under various seasons and geomagnetic activities

Global Navigation Satellite Systems (GNSS) have many applications in surveying, geodesy, and everyday life, so the accuracy of observations is very important. To have accurate results, many errors should be corrected, including ionospheric errors. Estimating the Differential Code Bias (DCB) and Total Electron Content (TEC) is essential to reduce ionospheric errors. This study's main aim is to determine how the combination of GPS (Global Positioning System) and GLONASS (GLObal NAvigation Satellite System) observations affect the estimation of DCB of satellites (SDCB) and receivers (RDCB) under the effects of geomagnetic storms and seasonal changes. The MATLAB-based software GR_DCB (GPS and GLONASS DCB estimation) was developed to estimate the SDCB and RDCB based on GPS and GLONASS observations. Theresults were tested using data from the International GNSS Service (IGS) network from nine stations and compared to previous studies to assess the effectiveness of the developed code. The findings are consistent with IGS products and more precise than previous studies that relied solely on GPS observations. An analysis of the effects of the geomagnetic storm on DCB variance is considered for June 22–23, 2015. During the geomagnetic storm, all GPS and GLONASS stations exhibited a fall in RDCB, led by a modest increase in some stations. The SDCB had no observed change on storm days compared with quiet days. The seasonal change affected GPS and GLONASS stations RDCB. Winter, which has the highest RDCB mean values, is also the season when a deviation in RDCB is the greatest. Autumn and Summer had the lowest dispersion in RDCB over the season and the lowest RDCB values.

Co-seismic deformation for the 2015 MW7.8 Gorkha earthquake (Nepal) using near-field GPS data

Seasonal variations and common mode errors affect the precision of the Global Positioning System (GPS) time series. In this paper, we explore to improve the precision of coordinate time series, thereby providing a better detection of weak or transient deformation signals, particularly co-seismic signals. Based on 97 GPS stations, including the campaign and continuous GPS stations in Nepal and southern Tibet, we first consider seasonal variations and common errors, then obtain co-seismic deformation of the 2015 Gorkha earthquake in Nepal and southern Tibet. Our co-seismic rupture model is characterized by a shallow ramp and a deeper detachment fault, in agreement with the relocated aftershock sequence. Our results indicate that the earthquake rupture is mainly distributed in the upper-crustal fault, and the maximum slip is up to 8.0 m at ∼15.0 km depth located in the approximate-80 km east of the epicenter. The average slip is more than 5 m, and the total modelled magnitude is MW7.84, consistent with the observed seismic moment. Our rupture model for the 2015 Gorkha earthquake suggests that the rupture zone is not only in the upper crustal Main Himalayan Thrust (MHT), but also spreads to the northern segment of the MHT.

Modern horizontal movements of tectonic blocks of the earth’s crust of Azerbaijan according to the data of the global positioning system (GPS) of the RSSC network

In order to identify the velocities of horizontal movements and directions of individual tectonic blocks of the earth’s crust, the Republican Seismological Survey Center of Azerbaijan (RSSC), starting from 2012, decided to create a network of GPS stations. Taking into account geomorphology, geotectonics, topography and taking into account the influence of external factors, sites for the construction of new GPS stations were chosen in various regions of our country. This new monitoring system consists of 24 Trimble GPS stations (USA) with a processing and analysis center in Baku, where all data from all regions where the stations were installed are received online. For the first time in the world, a GPS station was installed on the Superdeep Saatly well (8324 m) in the territory of the Republic of Azerbaijan in the Saatly region. On the basis of GPS space geodesy data and seismological data, the current geodynamic conditions of the territory of Azerbaijan for 2020-2021 were analyzed. The most important feature of the velocity field of horizontal motions is the decrease in velocity values perpendicular to the direction of the Greater Caucasus strike from south to north. The velocity field clearly illustrates the movement of the earth’s surface in the N-NE direction. In addition, within the Srednekura depression and in the Lesser Caucasus, there is a trend towards horizontal displacement, which is reflected in an increase in the speed of movement from west to east along the continuation of the ridge. It has been established that on the Absheron Peninsula the earth’s crust is shortening at a rate of ~ 5 mm/year. It was found that in 2020 the maximum values of horizontal velocities were noted at the stations of Aghdam, Lerik, Lankaran, Jalilabad, Fizuli and Saatly, and the average value of velocities throughout the republic was 7.3 mm/year.

A Novel Method to Improve the Estimation of Ocean Tide Loading Displacements for K1 and K2 Components with GPS Observations

The accurate estimation of ocean tide loading displacements is essential and necessary for geodesy, oceanic and geophysical studies. It is common knowledge that K1 and K2 tidal constituents estimated from Global Positioning System (GPS) observations are unsatisfactory because their tidal periods are nearly same to the revisit cycle or orbital period of GPS constellation. To date, this troublesome problem is not fully solved. In this paper, we revisit this important issue and develop a novel method based on the unique characteristic of tidal waves to separate GPS-system errors from astronomical K1/K2 tides. The well-known credo of smoothness indicates that tidal admittances of astronomical constituents in a narrow band can be expressed as smooth functions of tidal frequencies, while the interference of GPS-system errors seriously damages the smooth nature of observed tidal admittances. Via quadratic fitting, smooth functions of tidal frequencies for tidal admittances can be determined, thus, astronomical K1 and K2 tides can be interpolated using fitted quadratic functions. Three GPS stations are selected to demonstrate our method because of their typicality in terms of poor estimates of K1/K2 tidal parameters related to GPS-system errors. After removing GPS-systematical contributions based on our method, corrected K1/K2 tides at three GPS stations are much closer to the modeled K1/K2 tides from FES2014, which is one of the most accurate tide models. Furthermore, the proposed method can be easily applied to other areas to correct GPS-system errors because their smooth nature is valid for global tidal signals.

Early postseismic deformation of the 2018 Lombok, Indonesia, earthquake sequence constrained by GPS data

Global Positioning System (GPS) stations in Lombok, Indonesia showed postseismic displacement following the 2018 Lombok earthquake sequence which occurred on 28 July 2018 (Mw 6.4), 5 August 2018 (Mw 6.9), 9 August 2018 (Mw 5.9), and the 19 August 2018 (Mw 6.3 and Mw 6.9). This research has investigated the contribution of afterslip and viscoelastic relaxation during the one-month period after the mainshock on 19 August 2018. This study utilizes continuous GPS data available from 20 August 2018–19 September 2018. The analysis reveals that the afterslip was distributed at the shallower portion of the fault, complementary to the deeper coseismic slip of the mainshock. Viscoelastic relaxation, involving a gravitational Maxwell viscoelastic response with viscosity of 9.0 × 1017 Pa s, was estimated. This research also found that the depth of elastic upper crust in this region is 50 km. Observations made during the one-month period after the mainshock revealed that afterslip was responsible for most of the ongoing postseismic deformation. Although the viscoelastic relaxation contributed only insignificantly during the one-month period, this research shows that viscoelastic relaxation is expected to increase with time.

CGPS Record of Active Extension in Moroccan Meseta and Shortening in Atlasic Chains under the Eurasia-Nubia Convergence.

The northwest-southeast convergence of the Eurasian and Nubian (African) plates in the western Mediterranean region propagates inside the Nubian plate and affects the Moroccan Meseta and the neighboring Atlasic belt. Five continuous Global Positioning System (cGPS) stations were installed in this area in 2009 and provide significant new data, despite a certain degree of errors (between 0.5 and 1.2 mm year-1, 95% confidence) due to slow rates. The cGPS network reveals 1 mm year-1 North/South shortening accommodated within the High Atlas Mountains, and unexpected 2 mm year-1 north-northwest/south-southeast extensional-to-transtensional tectonics within the Meseta and the Middle Atlas, which have been quantified for the first time. Moreover, the Alpine Rif Cordillera drifts towards the south-southeast against its Prerifian foreland basins and the Meseta. In this context, the geological extension foreseen in the Moroccan Meseta and Middle Atlas agrees with a crustal thinning due to the combined effect of the anomalous mantle beneath both the Meseta and Middle-High Atlasic system, from which Quaternary basalts were sourced, and the roll-back tectonics in the Rif Cordillera. Overall, the new cGPS data provide reliable support for understanding the geodynamic mechanism that built the prominent Atlasic Cordillera, and reveal the heterogeneous present-day behavior of the Eurasia-Nubia collisional boundary.

Towards mitigating the effect of plasma bubbles on GPS positioning accuracy through wavelet transformation over Southeast Asian region

Ionospheric irregularities remain as a challenging concern among space scientists and engineers as it can pose severe threats to satellite-based services by introducing amplitude and phase scintillations in the transionospheric radio signals. The scintillations may cause degradation of the positioning, navigation, and timing (PNT) services or even complete system failure under extreme conditions. The present work focuses on understanding the ionospheric irregularities during the space weather event on May 12, 2021, witnessing the first strong geomagnetic storm in the 25th solar cycle. This particular event commenced around 13.00 UT, apparently altering the regular development of equatorial plasma bubbles around the local post-sunset terminator. We selected three global positioning system (GPS) stations, one at the near-magnetic equator (CUSV) and two at far low-latitude locations with a longitudinal separation (THKK and HWKS) over the Southeast Asian longitudes to investigate the characteristics of ionospheric plasma irregularities on the storm day. The results showed that the amplitude of ROTI was highest at the low-latitude CUSV, followed by the THKK and HKWS stations. The increased ROTI at CUSV is due to its latitudinal location close to the geomagnetic equator in the equatorial ionization anomaly (EIA) region which often witnesses more fluctuations than the inter-mediate latitudes. The strong TEC fluctuation occurrences were comparatively minimal at HWKS station on the storm day (May 12, 2021), whereas both intermediate and relatively higher TEC fluctuation occurrences were found at THKK and CUSV stations, respectively. Moreover, the occurrence rate of moderate irregularities was the highest at CUSV, followed by THKK and HKWS, while that of weak irregularities was maximum at HKWS, followed by THKK and CUSV. This happens because the systematic longitudinal time delay observed at the onset of ionospheric scintillations corresponds to the rise of PBs velocity at the magnetic equator that strongly depended upon the F-region dynamo electric fields in the east–west direction. Furthermore, the three-dimensional (3-D) positioning errors were estimated at a 30-sec interval to understand the impact of storm-induced irregularity on the positioning solution. An excellent agreement is realized between the ROTI pattern and positioning errors at all stations, irrespective of latitudinal extent from the magnetic equator. In order to model the amplitude of the scintillation index against the SNR measurements, the linear, quadratic, and cubic regression curve fittings are utilized that indicate the cubic polynomial manifesting the best fitted SNR measurements with the weak as well as moderate scintillation index. The continuous wavelet transformation (CWT) method was implemented to mitigate the ionospheric scintillation effects on positioning accuracy. The CWT estimation reveals the hidden information in positioning error due to the scintillation index, which makes it easy to understand the ionospheric scintillation effects on positioning. The attempt in this work is aligned with the efforts towards reliable PNT operations over equatorial and low latitudes.