Search Results (15)

A response of global seismic activity to the geomagnetic storms of St. Patrick’s Day (March 17) in 2013 and 2015 is investigated. These two storms occurred during nearly identical storm sudden commencement times and similar solar flux levels. We have revealed a rather similar pattern of the most substantial earthquakes that have occurred since these storms. Two major crust continental earthquakes, in Iran (M = 7.7), 16 April 2013, and in Nepal (M = 7.8), 25 April 2015, have occurred with a time delay of ~30 and ~39 days after geomagnetic storm onsets in 2013 and 2015, respectively. After that, the great and major deep-focused earthquakes occurred beneath the Sea of Okhotsk (M = 8.3, 24 May 2013, Russia) and the Pacific Ocean (M = 7.8, 30 May 2015, Japan) with a time delay of ~68 and ~74 days, respectively. Geomagnetic storm onsets occurred at 06:04 UT in 2013 and 04:48 UT in 2015. At this time, the high latitudinal areas of the longitudinal regions, in which the mentioned earthquakes occurred in the future, were located under the polar cusp, where the solar wind plasma has direct access to the Earth’s environment. An analysis of the remaining ten earthquakes with M ≥ 7.5, which occurred around the globe in 2013 and 2015, proved the above findings that seismic activity may respond to geomagnetic storm onset with a time delay from some days to some months. Full article

We report ground-based measurements of the atmospheric electric field (Ez = −potential gradient (PG)) and current density (Jz) that were conducted at two locations in Israel. One is at the Emilio Segre cosmic ray station located on Mt. Hermon (34.45° N, 2020 m AMSL) in northern Israel near the Syrian-Lebanon border, and the other is at the Wise astronomical observatory in the Negev desert highland plateau of southern Israel (31.18° N, 870 m AMSL). We searched for possible effects of strong, short-term solar events on the potential gradient and the vertical current density, as disruptions to the global electric circuit are often observed following strong solar events. The first case study (St. Patrick’s Day, 17 March 2015) was classified as the strongest event of 2015. The second case study (8 September 2017) was categorized as the strongest event of 2017 and one of the twenty strongest events on record to date. The results show that the electrical parameters measured at ground level at both stations were not affected during the two massive proton events and the ensuing geomagnetic storms. The magnetospheric shielding in lower latitudes is strong enough to shield against the flux of energetic particles from solar events, obscuring any impact that may be noticeable above the local daily variations induced by local meteorological conditions (aerosol concentrations, clouds, high humidity, and wind speed), which were investigated as well. Full article

Monitoring of ionospheric total electron content (TEC) was made possible with the help of satellite data, albeit in one dimension. However, ionospheric TEC maps can be produced from a collection of one-dimensional satellite data over a geographic area. Multiple mapping methods have been recognized; however, this study tried to test one of those methods: kriging interpolation. An algorithm was developed and used to reconstruct GIMs. The optimum number of stations and the semivariogram model were evaluated using GIM maps modeling 12 days of March 2015, accounting for different ionospheric conditions. This includes days of high scintillation and an ionospheric storm due to the St. Patrick’s Day geomagnetic storm of 2015. It was found that 12 stations and the linear semivariogram model had the least mean error in 5 days and had the least standard deviation in 7 days, making it the optimum parameter set. This optimum set was then used to map and analyze the ionosphere using actual satellite data from the Philippine Active Geodetic Network (PAGeNet). From this, it was observed that there is a north–south gradient in VTEC in the region during the day. The VTEC in the north reaches more than 100 TECU, and, in the south, generally around 60–90 TECU depending on the ionospheric condition. VTEC was at a minimum during the night when the VTEC level decreases to around 10 TECU. Full article

The aim of this paper is to statistically examine whether there are different patterns in daily numbers of deaths during the quiet periods of solar activity, in contrast to the periods of the strong solar storms. We considered three periods of solar storms (storm of 14 July 2000 Bastille Day Event, storm of 28 October 2003 Halloween Solar Storms, and storm of 17 March 2015 St. Patrick’s Day event) and three periods of continuous very low solar activity (13 September–24 October 1996, 21 July–20 August 2008, and 31 July–31 August 2009) during the Solar Cycles No. 23 and No. 24. In particular, we focus on diseases of the nervous system (group VI from ICD-10) and diseases of the circulatory system (group IX from ICD-10) separately for both sexes and two age groups (under 39 and 40+). We demonstrate that in the resulting graphical models there was a connection between the daily number of deaths and all indices of solar and geomagnetic activity in periods of low solar activity in contrast to periods of strong solar storms in some monitored groups according to age, sex, and group of diagnosis. Full article

This study presents a new modeling approach that aims for long time predictions (more than 12 h) of ionospheric disturbances driven by solar storm events. The proposed model shall run in an operational framework to deliver fast and precise localized warnings for these disturbances in the future. The solar wind data driven approach uses a data base of historical solar storm impacts covering two solar cycles to reconstruct future events and resulting ionospheric disturbances. The basic components of the model are presented and discussed in this study, and the strengths of the reconstruction based on historical events are presented by showing the good correlations for predicted and observed geomagnetic activity. Initial results on the ionospheric response are discussed for all historical events using global total electron content (GTEC) and in more detail using total electron content (TEC) maps for two specific case studies (including the St. Patrick’s Day geomagnetic storm during the 17 March 2015). Average root mean square error (RMSE) values of 3.90 and 5.21 TECU are calculated for these cases confirming good results for the current configuration of the model. Possible future improvements of the individual model parts, as well as the planned extensions and applications are discussed in detail. Full article

Global Navigation Satellite System (GNSS) Radio Occultation (RO) has provided high-quality atmospheric data assimilated in Numerical Weather Prediction (NWP) models and climatology studies for more than 20 years. In the satellite–satellite GNSS-RO geometry, the measurements are susceptible to ionospheric scintillation depending on the solar and geomagnetic activity, seasons, geographical location and local time. This study investigates the application of the Support Vector Machine (SVM) algorithm in developing an automatic detection model of F-layer scintillation in GNSS-RO measurements using power spectral density (PSD). The model is intended for future analyses on the influence of space weather and solar activity on RO data products over long time periods. A novel data set of occultations is used to train the SVM algorithm. The data set is composed of events at low latitudes on 15–20 March 2015 (St. Patrick’s Day geomagnetic storm, high solar flux) and 14–19 May 2018 (quiet period, low solar flux). A few conditional criteria were first applied to a total of 5340 occultations to define a set of 858 scintillation candidates. Models were trained with scintillation indices and PSDs as training features and were either linear or Gaussian kernel. The investigations also show that besides the intensity PSD, the (excess) phase PSD has a positive contribution in increasing the detection of true positives. Full article

This paper presents a comparison of the vertical total electron content (vTEC) estimated over Italy using two different approaches: the GPS Global Ionosphere Maps (GIMs) and the so-called “calibration technique” developed by Ciraolo in 2007. The study has been carried out at a regional level by considering three Italian dual-frequency stations of the GPS permanent network “Rete Integrata Nazionale GPS (RING)”. The GPS receivers are permanently installed at Madesimo (geographical coordinates: 46.5 N, 9.4 E), Rome (geographical coordinates: 41.8 N, 12.5 E) and Resuttano (geographical coordinates: 37.7 N, 14.1 E), respectively in the north, center and south of Italy. Time windows selected for the analysis include periods of both low (July 2008 to June 2009) and high (September 2013 to August 2014) solar activity. The two datasets have also been studied considering both quiet and disturbed geomagnetic activity conditions. Moreover, the effects of an extreme geomagnetic storm have been investigated in March 2015 when the well-known St. Patrick storm occurred. Overall, GIM estimated values are always higher than those calibrated by the Ciraolo procedure for all the considered datasets. The differences between the two methods increase as the latitude decreases, and they increase as the solar activity intensifies. The outcomes of this study shall be helpful when applying GlMs at a regional level. Full article

The ionosphere is a significant component of the geospace environment. Storm-induced ionospheric anomalies severely affect the performance of Global Navigation Satellite System (GNSS) Positioning, Navigation, and Timing (PNT) and human space activities, e.g., the Earth observation, deep space exploration, and space weather monitoring and prediction. In this study, we present and discuss the multi-scale ionospheric anomalies monitoring over China using the GNSS observations from the Crustal Movement Observation Network of China (CMONOC) during the 2015 St. Patrick’s Day storm. Total Electron Content (TEC), Ionospheric Electron Density (IED), and the ionospheric disturbance index are used to monitor the storm-induced ionospheric anomalies. This study finally reveals the occurrence of the large-scale ionospheric storms and small-scale ionospheric scintillation during the storm. The results show that this magnetic storm was accompanied by a positive phase and a negative phase ionospheric storm. At the beginning of the main phase of the magnetic storm, both TEC and IED were significantly enhanced. There was long-duration depletion in the topside ionospheric TEC during the recovery phase of the storm. This study also reveals the response and variations in regional ionosphere scintillation. The Rate of the TEC Index (ROTI) was exploited to investigate the ionospheric scintillation and compared with the temporal dynamics of vertical TEC. The analysis of the ROTI proved these storm-induced TEC depletions, which suppressed the occurrence of the ionospheric scintillation. To improve the spatial resolution for ionospheric anomalies monitoring, the regional Three-Dimensional (3D) ionospheric model is reconstructed by the Computerized Ionospheric Tomography (CIT) technique. The spatial-temporal dynamics of ionospheric anomalies during the severe geomagnetic storm was reflected in detail. The IED varied with latitude and altitude dramatically; the maximum IED decreased, and the area where IEDs were maximum moved southward. Full article

A statistical analysis of the relation between exceptional solar events and daily numbers of deaths in the Czech Republic is presented. In particular, we concentrate on diseases of the nervous system (group VI from ICD-10—International Statistical Classification of Diseases and Related Health Problems 10th Revision) and diseases of the circulatory system (group IX from ICD-10). We demonstrate that the neurological diseases exhibit greater instability during the period of rising and falling solar activity. We study the daily numbers of deaths, separately for both sexes and two age groups (under 39 and 40+), during the Solar Cycles No. 23 and No. 24. We focus on exceptionally strong solar events in this period, such as the “Bastille Day event” on 14 July 2000, “Halloween solar storm” on 28 October 2003, and events on 7 January 1997, 2 April 2000, and on 7 September 2005. Special attention is paid to “St. Patrick’s Day storm” on 17 March 2015, the strongest geomagnetic storm of the Solar Cycle No. 24 that occurred following a coronal mass ejection (CME). We investigate the changes in the daily numbers of deaths during 1 month before and 1 month after these exceptional solar events. We take specific storm dynamics of their geophysical parameters into consideration. It has been verified that, for diseases of the nervous system, women are generally more sensitive than men. On the contrary, this differences between men and women have not been found for diseases of the circulatory system. Our findings suggest that the impact of the hazardous space weather conditions on human health depends on the specific dynamic and strength of the solar storm. Full article

In solar cycle 24, the strongest geomagnetic storm took place on 17 March 2015, when the geomagnetic activity index was as high as −223 nT. To verify the impact that the storm had on the Global Navigation Satellite System (GNSS)’s positioning accuracy and precision, we used 30-s observations from 15 reference stations located in Central Europe. For each of them, we applied kinematic precise point positioning (PPP) using gLAB software for the day of the storm and, for comparison, for a selected quiet day (13 March 2015). Based on the conducted analyses, we found out that the position root mean square (RMS) values on the day of the geomagnetic storm were significantly high and amounted to several dozen centimeters. The average RMS for the altitude coordinates was 0.58 m between 12:00 and 24:00 (GPS time), and 0.37 and 0.26 m for directions North and East, respectively. The compromised accuracy level was caused by a sudden decrease in the number of satellites used for calculations. This was due to a high number of cycle slips (CSs) detected during this period. The occurrence of these effects was strictly correlated with the appearance of traveling ionospheric disturbances (TIDs). This was proven by analyzing changes in the total electron content (TEC) estimated for each station–satellite pair. Full article

The continuously expanding toolbox of nonlinear time series analysis techniques has recently highlighted the importance of dynamical complexity to understand the behavior of the complex solar wind–magnetosphere–ionosphere–thermosphere coupling system and its components. Here, we apply new such approaches, mainly a series of entropy methods to the time series of the Earth’s magnetic field measured by the Swarm constellation. We show successful applications of methods, originated from information theory, to quantitatively study complexity in the dynamical response of the topside ionosphere, at Swarm altitudes, focusing on the most intense magnetic storm of solar cycle 24, that is, the St. Patrick’s Day storm, which occurred in March 2015. These entropy measures are utilized for the first time to analyze data from a low-Earth orbit (LEO) satellite mission flying in the topside ionosphere. These approaches may hold great potential for improved space weather nowcasts and forecasts. Full article

Geostatistical Analyst is a set of advanced tools for analysing spatial data and generating surface models using statistical and deterministic methods available in ESRI ArcMap software. It enables interpolation models to be created on the basis of data measured at chosen points. The software also provides tools that enable analyses of the data variability, setting data limits and checking global trends, as well as creating forecast maps, estimating standard error and probability, making various surface visualisations, and analysing spatial autocorrelation and correlation between multiple data sets. The data can be interpolated using deterministic methods providing surface continuity, and also by stochastic techniques like kriging, based on a statistical model considering data autocorrelation and providing expected interpolation errors. These properties of Geostatistical Analyst make it a valuable tool for modelling and analysing the Earth’s ionosphere. Our research aims to test its applicability for studying the ionosphere, and ionospheric disturbances in particular. As raw source data, we use Global Navigation Satellite Systems (GNSS)-derived ionospheric total electron content. This paper compares ionosphere models (maps) developed using various interpolation methods available in Geostatistical Analyst. The comparison is based on several indicators that can provide the statistical characteristics of an interpolation error. In this contribution, we use our own method, the parametric assessment of the quality of estimation (MPQE). Here, we present analyses and a discussion of the modelling results for various states of the ionosphere: On the disturbed day of the St Patrick’s Day geomagnetic storm of 2015, one quiet day before the storm and one day after its occurrence, reflecting the ionosphere recovery phase. Finally, the optimal interpolation method is selected and presented. Full article

The ionosphere is one of the largest error sources in GNSS (Global Navigation Satellite Systems) applications and can cause up to several meters of error in positioning. Especially for single-frequency users, who cannot correct the ionospheric delay, the information about the state of the ionosphere is mandatory. Dual- and multi-frequency GNSS users, on the other hand, can correct the ionospheric effect on their observations by linear combination. However, real-time applications such as autonomous driving or precision farming, require external high accuracy corrections for fast convergence. Mostly, this external information is given in terms of grids or coefficients of the vertical total electron content (VTEC). Globally distributed GNSS stations of different networks, such as the network of the International GNSS Services (IGS), provide a large number of multi-frequency observations which can be used to determine the state of the ionosphere. These data are used to generate Global Ionosphere Maps (GIM). Due to the inhomogeneous global distribution of GNSS real-time stations and especially due to the large data gaps over oceanic areas, the global VTEC models are usually limited in their spatial and spectral resolution. Most of the GIMs are mathematically based on globally defined radial basis functions, i.e., spherical harmonics (SH), with a maximum degree of 15 and provided with a spatial resolution of ${2.5}^{°}\times 5^{°}$ in latitude and longitude, respectively. Regional GNSS networks, however, offer dense clusters of observations, which can be used to generate regional VTEC solutions with a higher spectral resolution. In this study, we introduce a two-step model (TSM) comprising a global model as the first step and a regional model as the second step. We apply polynomial and trigonometric B-spline functions to represent the global VTEC. Polynomial B-splines are used for modelling the finer structures of VTEC within selected regions, i.e., the densification areas. The TSM provides both, a global and a regional VTEC map at the same time. In order to study the performance, we apply the developed approach to hourly data of the global IGS network as well as the EUREF network of the European region for St. Patrick storm in March 2015. For the assessment of the generated maps, we use the dSTEC analysis and compare both maps with different global and regional products from the IGS Ionosphere Associated Analysis Centers, e.g., the global product from CODE (Berne, Switzerland) and from UPC (Barcelona, Spain), as well as the regional maps from ROB (Brussels, Belgium). The assessment shows a significant improvement of the regional VTEC representation in the form of the generated TSM maps. Among all other products used for comparison, the developed regional one is of the highest accuracy within the selected time span. Since the numerical tests are performed using hourly data with a latency of one to two hours, the presented procedure is seen as an intermediate step for the generation of high precision regional real-time corrections for modern applications. Full article

Dual-frequency GNSS data processing is currently one of the most useful techniques for sounding the ionosphere. Hence, this work was aimed at the evaluation of ground-based GNSS data for the continuous monitoring of polar patches in both hemispheres. In this contribution, we proposed to use epoch-wise relative STEC values in order to detect these structures. The applied indicator is defined as a difference between an undifferenced geometry-free linear combination of GNSS signals and the background ionospheric variations, which were assessed with an iterative algorithm of four-degree polynomial fitting. The occurrence of patches during the St. Patrick geomagnetic storm was performed for validation purposes. The first part of the work confirmed the applicability of the relative STEC values for such investigations. On the other hand, it also revealed the limitations related to the inhomogeneous distribution of stations, which may affect the results in both hemispheres. This was confirmed with a preliminary cross-evaluation of GNSS and in situ SWARM datasets. Apart from the periods with a well-established coincidence, the opposite situation, when both methods indicated different parts of the polar ionosphere, was also observed. The second part of this contribution depicted the feasibility of continuous patch detection for both regions, and thus the interhemispheric comparison of the analyzed structures. It has demonstrated the strong disproportion between patches in the northern and southern hemispheres. This discrepancy seems to be related to the different amount of plasma propagating from the dusk sector, which is justified by the values of relative STEC at mid-latitudes. The observed structures are also strongly dependent on the orientation of the interplanetary magnetic field. Full article

The technique of the orthogonal projection of ionosphere electronic content variations for mapping total electron content (TEC) allows us to visualize ionospheric irregularities. For the reconstruction of global ionospheric characteristics, numerous global navigation satellite system (GNSS) receivers located in different regions of the Earth are used as sensors. We used dense GNSS networks in central Europe to detect and investigate a special type of plasma inhomogeneities, called travelling ionospheric disturbances (TID). Such use of GNSS sensors allows us to reconstruct the main TID parameters, such as spatial dimensions, velocities, and directions of their movement. The paper gives examples of the restoration of dynamic characteristics of ionospheric irregularities for quiet and disturbed geophysical conditions. Special attention is paid to the dynamics of ionospheric disturbances stimulated by the magnetic storms of two St. Patrick’s Days (17 March 2013 and 2015). Additional opportunities for the remote sensing of the ionosphere with the use of dense regional networks of GNSS receiving sensors have been noted too. Full article