scholarly journals Pre-Earthquake Ionospheric Anomalies Associated with the 2015 Gorkha Earthquake of Nepal Detected by GPS-TEC Measurements

Author(s):  
Monika Karki ◽  
Ashok Silwal ◽  
Narayan Prasad Chapagain ◽  
Prakash Poudel ◽  
Sujan Prasad Gautam ◽  
...  

Abstract The present study analyses the variations in the ionospheric total electron content (TEC) prior to and during the 2015 Gorkha Earthquake in Nepal (Mw = 7.8) on 25 April 2015, utilising data from the widely distributed Global Positioning System (GPS) network. This study aimed to determine the association between ionospheric TEC anomalies and the occurrence of earthquakes. The finding shows that anomalous TEC changes occurred several days to a few hours prior to the major impending events. The results reveal that deviations in vertical total electron content (VTEC) at distant locations from the epicentre are less than those observed at the epicentre, implying that variation in ionospheric VTEC is nearly inversely proportional to the distance of GPS stations from the epicentre. In view of the solar-terrestrial environment, the pre-earthquake ionospheric anomalies could be associated with the 2015 Gorkha Earthquake. The VTEC anomaly was identified when it crosses the upper bound (UB) or lower bound (LB). The outcomes additionally show that TEC variation was dominant in the vicinity of the earthquake epicentre. We also observed contrast in TEC throughout the globe using global ionospheric maps at regular 2-hour UT intervals, the day before, during and after the earthquake. As a result, we observed that areas heavily influenced by TEC were found to be transposed from eastern sectors to western sectors through the equatorial plane. TEC Maps indicate that most of the Indian regions, Northern China, Nepal, Bhutan, were heavily affected, indicating the earthquake's onset influence on the day of the event. Furthermore, we examined the cross-correlation of the SGOC station's TEC with the rest of the stations and discovered that the correlation increased gradually with epicentral distance from the surrounding stations, which was an intriguing result.

2013 ◽  
Vol 19 (2) ◽  
pp. 227-246 ◽  
Author(s):  
Wagner Carrupt Machado ◽  
Edvaldo Simões da Fonseca Junior

Uma forma de se prever o conteúdo total de elétrons na direção vertical (VTEC - Vertical Total Electron Content) usando a arquitetura de redes neurais artificiais (RNA) denominada de perceptrons de múltiplas camadas (MLP - MultipLayer Percetrons) é apresentada e avaliada nesta pesquisa. As entradas do modelo foram definidas como sendo a posição dos pontos ionosféricos (IPP - Ionospheric Pierce Point) e o tempo universal (TU), enquanto que a saída é o VTEC. As variações sazonais e de períodos mais longos são levadas em conta através da atualização do treinamento diariamente. Testes foram conduzidos sobre uma área que abrange o Brasil e sua vizinhança considerando períodos de alta e baixa atividade solar. As RNA foram treinadas utilizando informações dos mapas globais da ionosfera (GIM - Global Ionospheric Maps) produzidos pelo serviço internacional do GNSS (IGS - International GNSS Service) das 72 horas anteriores à época de início da previsão. As RNA treinadas foram utilizadas para prever o VTEC por 72 horas (VTEC RNA). Os VTEC RNA foram comparados com os VTEC contidos nos GIM (VTEC GIM). A raiz do erro médio quadrático (RMS) da diferença entre o VTEC GIM e o VTEC RNA variou de 1,4 a 10,7 unidades de TEC (TECU). O erro relativo mostra que a RNA proposta foi capaz de prever o VTEC com 70 a 85% de acerto.


2017 ◽  
Vol 21 (6) ◽  
pp. 1599-1612 ◽  
Author(s):  
Weiping Jiang ◽  
Yifang Ma ◽  
Xiaohui Zhou ◽  
Zhao Li ◽  
Xiangdong An ◽  
...  

2008 ◽  
Vol 26 (4) ◽  
pp. 893-903 ◽  
Author(s):  
◽  
◽  
◽  

Abstract. Sometimes the ionospheric total electron content (TEC) is significantly enhanced during low geomagnetic activities before storms. In this article, we investigate the characteristics of those interesting TEC enhancements using regional and global TEC data. We analyzed the low-latitude TEC enhancement events that occurred around longitude 120° E on 10 February 2004, 21 January 2004, and 4 March 2001, respectively. The TEC data are derived from regional Global Positioning System (GPS) observations in the Asia/Australia sector as well as global ionospheric maps (GIMs) produced by Jet Propulsion Laboratory (JPL). Strong enhancements under low geomagnetic activity before the storms are simultaneously presented at low latitudes in the Asia/Australia sector in regional TEC and JPL GIMs. These TEC enhancements are shown to be regional events with longitudinal and latitudinal extent. The regions of TEC enhancements during these events are confined at narrow longitude ranges around longitude 120° E. The latitudinal belts of maxima of enhancements locate around the northern and southern equatorial ionization anomaly (EIA) crests, which are consistent with those low-latitude events presented by Liu et al. (2008). During the 4 March 2001 event, the total plasma density Ni observed by the Defense Meteorological Satellite Program (DMSP) spacecraft F13 at 840 km altitude are of considerably higher values on 4 March than on the previous day in the TEC enhanced regions. Some TEC enhancement events are possibly due to contributions from auroral/magnetospheric origins; while there are also quasi-periodic enhancement events not related to geomagnetic activity and associated probably with planetary wave type oscillations (e.g. the 6 January 1998 event). Further investigation is warrented to identify/separate contributions from possible sources.


2020 ◽  
Vol 12 (11) ◽  
pp. 1822
Author(s):  
Eren Erdogan ◽  
Michael Schmidt ◽  
Andreas Goss ◽  
Barbara Görres ◽  
Florian Seitz

The Kalman filter (KF) is widely applied in (ultra) rapid and (near) real-time ionosphere modeling to meet the demand on ionosphere products required in many applications extending from navigation and positioning to monitoring space weather events and naturals disasters. The requirement of a prior definition of the stochastic models attached to the measurements and the dynamic models of the KF is a drawback associated with its standard implementation since model uncertainties can exhibit temporal variations or the time span of a given test data set would not be large enough. Adaptive methods can mitigate these problems by tuning the stochastic model parameters during the filter run-time. Accordingly, one of the primary objectives of our study is to apply an adaptive KF based on variance component estimation to compute the global Vertical Total Electron Content (VTEC) of the ionosphere by assimilating different ionospheric GNSS measurements. Secondly, the derived VTEC representation is based on a series expansion in terms of compactly supported B-spline functions. We highlight the morphological similarity of the spatial distributions and the magnitudes between VTEC values and the corresponding estimated B-spline coefficients. This similarity allows for deducing physical interpretations from the coefficients. In this context, an empirical adaptive model to account for the dynamic model uncertainties, representing the temporal variations of VTEC errors, is developed in this work according to the structure of B-spline coefficients. For the validation, the differential slant total electron content (dSTEC) analysis and a comparison with Jason-2/3 altimetry data are performed. Assessments show that the quality of the VTEC products derived by the presented algorithm is in good agreement, or even more accurate, with the products provided by IGS ionosphere analysis centers within the selected periods in 2015 and 2017. Furthermore, we show that the presented approach can be applied to different ionosphere conditions ranging from very high to low solar activity without concerning time-variable model uncertainties, including measurement error and process noise of the KF because the associated covariance matrices are computed in a self-adaptive manner during run-time.


Sensors ◽  
2019 ◽  
Vol 19 (5) ◽  
pp. 1138 ◽  
Author(s):  
Liang Zhang ◽  
Yibin Yao ◽  
Wenjie Peng ◽  
Lulu Shan ◽  
Yulin He ◽  
...  

The prevalence of real-time, low-cost, single-frequency, decimeter-level positioning has increased with the development of global navigation satellite systems (GNSSs). Ionospheric delay accounts for most errors in real-time single-frequency GNSS positioning. To eliminate ionospheric interference in real-time single-frequency precise point positioning (RT-SF-PPP), global ionospheric vertical total electron content (VTEC) product is designed in the next stage of the International GNSS Service (IGS) real-time service (RTS). In this study, real-time generation of a global ionospheric map (GIM) based on IGS RTS is proposed and assessed. There are three crucial steps in the process of generating a real-time global ionospheric map (RTGIM): estimating station differential code bias (DCB) using the precise point positioning (PPP) method, deriving slant total electron content (STEC) from PPP with raw observations, and modeling global vertical total electron content (VTEC). Experiments were carried out to validate the algorithm’s effectiveness. First, one month’s data from 16 globally distributed IGS stations were used to validate the performance of DCB estimation with the PPP method. Second, 30 IGS stations were used to verify the accuracy of static PPP with raw observations. Third, the modeling of residuals was assessed in high and quiet ionospheric activity periods. Afterwards, the quality of RTGIM products was assessed from two aspects: (1) comparison with the Center for Orbit Determination in Europe (CODE) global ionospheric map (GIM) products and (2) determination of the performance of RT-SF-PPP with the RTGIM. Experimental results show that DCB estimation using the PPP method can realize an average accuracy of 0.2 ns; static PPP with raw observations can achieve an accuracy of 0.7, 1.2, and 2.1 cm in the north, east, and up components, respectively. The average standard deviations (STDs) of the model residuals are 2.07 and 2.17 TEC units (TECU) for moderate and high ionospheric activity periods. Moreover, the average root-mean-square (RMS) error of RTGIM products is 2.4 TECU for the one-month moderate ionospheric period. Nevertheless, for the high ionospheric period, the RMS is greater than the RMS in the moderate period. A sub-meter-level horizontal accuracy and meter-level vertical accuracy can be achieved when the RTGIM is employed in RT-SF-PPP.


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