scholarly journals Magnetic Field and Electron Density Data Analysis from Swarm Satellites Searching for Ionospheric Effects by Great Earthquakes: 12 Case Studies from 2014 to 2016

Atmosphere ◽  
2019 ◽  
Vol 10 (7) ◽  
pp. 371 ◽  
Author(s):  
Angelo De Santis ◽  
Dedalo Marchetti ◽  
Luca Spogli ◽  
Gianfranco Cianchini ◽  
F. Javier Pavón-Carrasco ◽  
...  

We analyse Swarm satellite magnetic field and electron density data one month before and one month after 12 strong earthquakes that have occurred in the first 2.5 years of Swarm satellite mission lifetime in the Mediterranean region (magnitude M6.1+) or in the rest of the world (M6.7+). The search for anomalies was limited to the area centred at each earthquake epicentre and bounded by a circle that scales with magnitude according to the Dobrovolsky’s radius. We define the magnetic and electron density anomalies statistically in terms of specific thresholds with respect to the same statistical quantity along the whole residual satellite track (|geomagnetic latitude| ≤ 50°, quiet geomagnetic conditions). Once normalized by the analysed satellite tracks, the anomalies associated to all earthquakes resemble a linear dependence with earthquake magnitude, so supporting the statistical correlation with earthquakes and excluding a relationship by chance.

2020 ◽  
Author(s):  
Angelo De Santis ◽  

<p>Analysing ionospheric electron density and magnetic field data from several years of the <em>Swarm</em> three-satellite mission we define a dataset of anomalies statistically.  We then use a superposed epoch approach to study the possible relation with a corresponding dataset of earthquakes occurred in the same space-time domain. Two statistical quantities <em>d</em> and <em>n</em> are then established comparing the statistics of the real analyses with simulations to assess the effectiveness of the largest concentrations of anomalies as ionospheric precursors. In detail, <em>d</em> would show how much the real maximum concentration is above the expected typical maximum concentration of a random anomaly distribution; while <em>n</em> value measures how much the largest concentration deviates with respect a typical random deviation: the larger are the <em>d</em> and <em>n</em> values, the more the results of the analysis applied to real data deviate from randomness. The best cases for which the real analyses are well distinct from random simulations are selected when <em>d</em>≥1.5, because the anomaly density is equal to or larger than 50% of random distribution, and <em>n</em>≥4, because the probability to be random is equal to or less than 0.1%.  This is the case of Y magnetic field component with a search in the Dobrovolsky area around each considered earthquake epicentre. The electron density is slightly less effective in the correlation with earthquakes, but still better than a homogeneous random distribution of anomalies.</p>


2019 ◽  
Vol 177 (1) ◽  
pp. 305-319 ◽  
Author(s):  
Dedalo Marchetti ◽  
Angelo De Santis ◽  
Serena D’Arcangelo ◽  
Federica Poggio ◽  
Shuanggen Jin ◽  
...  

Geosciences ◽  
2020 ◽  
Vol 10 (12) ◽  
pp. 502
Author(s):  
Dedalo Marchetti ◽  
Angelo De Santis ◽  
Saioa A. Campuzano ◽  
Maurizio Soldani ◽  
Alessandro Piscini ◽  
...  

This work presents an analysis of the ESA Swarm satellite magnetic data preceding the Mw = 7.1 California Ridgecrest earthquake that occurred on 6 July 2019. In detail, we show the main results of a procedure that investigates the track-by-track residual of the magnetic field data acquired by the Swarm constellation from 1000 days before the event and inside the Dobrovolsky’s area. To exclude global geomagnetic perturbations, we select the data considering only quiet geomagnetic field time, defined by thresholds on Dst and ap geomagnetic indices, and we repeat the same analysis in two comparison areas at the same geomagnetic latitude of the Ridgecrest earthquake epicentre not affected by significant seismicity and in the same period here investigated. As the main result, we find some increases of the anomalies in the Y (East) component of the magnetic field starting from about 500 days before the earthquake. Comparing such anomalies with those in the validation areas, it seems that the geomagnetic activity over California from 222 to 168 days before the mainshock could be produced by the preparation phase of the seismic event. This anticipation time is compatible with the Rikitake empirical law, recently confirmed from Swarm satellite data. Furthermore, the Swarm Bravo satellite, i.e., that one at highest orbit, passed above the epicentral area 15 min before the earthquake and detected an anomaly mainly in the Y component. These analyses applied to the Ridgecrest earthquake not only intend to better understand the physical processes behind the preparation phase of the medium-large earthquakes in the world, but also demonstrate the usefulness of a satellite constellation to monitor the ionospheric activity and, in the future, to possibly make reliable earthquake forecasting.


2019 ◽  
Vol 9 (1) ◽  
Author(s):  
A. De Santis ◽  
D. Marchetti ◽  
F. J. Pavón-Carrasco ◽  
G. Cianchini ◽  
L. Perrone ◽  
...  

AbstractThe study of the preparation phase of large earthquakes is essential to understand the physical processes involved, and potentially useful also to develop a future reliable short-term warning system. Here we analyse electron density and magnetic field data measured by Swarm three-satellite constellation for 4.7 years, to look for possible in-situ ionospheric precursors of large earthquakes to study the interactions between the lithosphere and the above atmosphere and ionosphere, in what is called the Lithosphere-Atmosphere-Ionosphere Coupling (LAIC). We define these anomalies statistically in the whole space-time interval of interest and use a Worldwide Statistical Correlation (WSC) analysis through a superposed epoch approach to study the possible relation with the earthquakes. We find some clear concentrations of electron density and magnetic anomalies from more than two months to some days before the earthquake occurrences. Such anomaly clustering is, in general, statistically significant with respect to homogeneous random simulations, supporting a LAIC during the preparation phase of earthquakes. By investigating different earthquake magnitude ranges, not only do we confirm the well-known Rikitake empirical law between ionospheric anomaly precursor time and earthquake magnitude, but we also give more reliability to the seismic source origin for many of the identified anomalies.


2020 ◽  
Author(s):  
Fabricio Prol ◽  
Mainul Hoque

<p>The plasmasphere is a region of continuous study due to some open questions related to the plasmaspheric internal dynamics, boundaries, and coupling processes with the magnetosphere and ionosphere, in particular during space weather events. Given such interests, the results of a new tomographic method to estimate the plasmaspheric electron density will be presented. The tomographic reconstruction is applied using measurements of Total Electron Content (TEC) from the Global Positioning System (GPS) receivers aboard the Constellation Observing System for Meteorology, Ionosphere, and Climate / Formosa Satellite Mission 3 (COSMIC/FORMOSAT-3). Despite relevant challenges imposed by the orbital geometry to obtain stable electron density reconstructions of a large area such as the plasmasphere, the developed approach was capable of representing the natural variability of the plasma ambient in terms of geographic/geomagnetic latitude, altitude, solar activity, season, and local time. The quality assessment was carried out using two years of in-situ electron density measurements from spacecraft deployed by the Defense Meteorological Satellite Program (DMSP). Our investigation revealed that improvements over 20% can be achieved for electron density specification by TEC data assimilation into background ionization.</p>


2019 ◽  
Vol 5 (2) ◽  
pp. 101-108 ◽  
Author(s):  
Виктор Захаров ◽  
Viktor Zakharov ◽  
Вячеслав Пилипенко ◽  
Vyacheslav Pilipenko ◽  
Валерий Грушин ◽  
...  

The article considers the influence of large atmospheric processes on the ionosphere by the example of tropical typhoon Vongfong 2014. We use data obtained from three SWARM satellite missions (450–500 km altitude). We discuss two possible mechanisms of transfer of atmospheric disturbances to ionospheric heights. The first mechanism is the generation of acoustic-gravity waves (AGWs); the second mechanism considers the excitation of electric fields in the atmosphere. We propose new techniques for detecting the ionospheric response to AGW, which rely on low-orbit satellite data. The first technique is based on determination of relative electron density variations in the frequency band from 15 to 150–180 s, corresponding to certain scales of AGW. The second technique estimates space-time derivatives of the electron density, measured by two nearby SWARM satellites. We present and estimate the characteristic magnitudes of ionospheric response effects, their localization and spatial-temporal characteristics for the large tropical cyclone under study.


2019 ◽  
Author(s):  
Sharon Aol ◽  
Stephan Buchert ◽  
Edward Jurua

Abstract. During the night, in the F-region, equatorial ionospheric irregularities manifest as plasma depletions observed by satellites and may cause radio signals to fluctuate. In this study, the distribution characteristics of ionospheric F-region irregularities in the low latitudes were investigated using 16 Hz electron density observations made by the faceplate on board Swarm satellites of the European Space Agency (ESA). The study covers the period from October 2014 to October 2018 when the 16 Hz electron density data were available. For comparison, both the absolute (ΔNe) and relative (ΔNe/Ne) density perturbations were used to quantify the level of ionospheric irregularities. The two methods generally reproduced the local time, seasonal and longitudinal distribution of equatorial ionospheric irregularities as shown in earlier studies, demonstrating the ability of Swarm 16 Hz electron density data. A difference between the two methods was observed based on the latitudinal distribution of ionospheric irregularities where ΔNe showed a symmetrical distribution about the magnetic equator, whereas ΔNe/Ne showed a magnetic equator centered Gaussian distribution. High values of ΔNe and ΔNe/Ne were observed in spatial bins with steep gradients of electron density from a longitudinal and seasonal perspective. The response of ionospheric irregularities to geomagnetic and solar activities was also investigated using Kp index and solar radio flux index (F10.7), respectively. A weak positive correlation was obtained between the occurrence of ionospheric irregularities and Kp index, irrespective of the method adopted to quantify the irregularities. In general, both ΔNe and ΔNe/Ne showed a weak positive correlation with F10.7. However, a higher positive correlation was obtained between ΔNe and F10.7 compared to ΔNe/Ne. Using the high-resolution faceplate data, we were able to identify ionospheric irregularities of scales of only a few hundreds of meters.


2020 ◽  
Vol 38 (1) ◽  
pp. 243-261 ◽  
Author(s):  
Sharon Aol ◽  
Stephan Buchert ◽  
Edward Jurua

Abstract. During the night, in the F-region, equatorial ionospheric irregularities manifest as plasma depletions observed by satellites, and they may cause radio signals to fluctuate. In this study, the distribution characteristics of ionospheric F-region irregularities in the low latitudes were investigated using 16 Hz electron density observations made by a faceplate which is a component of the electric field instrument (EFI) onboard Swarm satellites of the European Space Agency (ESA). The study covers the period from October 2014 to October 2018 when the 16 Hz electron density data were available. For comparison, both the absolute (dNe) and relative (dNe∕Ne) density perturbations were used to quantify the level of ionospheric irregularities. The two methods generally reproduced the local-time (LT), seasonal and longitudinal distribution of equatorial ionospheric irregularities as shown in earlier studies, demonstrating the ability of Swarm 16 Hz electron density data. A difference between the two methods was observed based on the latitudinal distribution of ionospheric irregularities where (dNe) showed a symmetrical distribution about the magnetic equator, while dNe∕Ne showed a magnetic-equator-centred Gaussian distribution. High values of dNe and dNe∕Ne were observed in spatial bins with steep gradients of electron density from a longitudinal and seasonal perspective. The response of ionospheric irregularities to geomagnetic and solar activities was also investigated using Kp index and solar radio flux index (F10.7), respectively. The reliance of dNe∕Ne on solar and magnetic activity showed little distinction in the correlation between equatorial and off-equatorial latitudes, whereas dNe showed significant differences. With regard to seasonal and longitudinal distribution, high dNe and dNe∕Ne values were often found during quiet magnetic periods compared to magnetically disturbed periods. The dNe increased approximately linearly from low to moderate solar activity. Using the high-resolution faceplate data, we were able to identify ionospheric irregularities on the scale of only a few hundred of metres.


2021 ◽  
Author(s):  
Jose van den IJssel ◽  
Christian Siemes ◽  
Pieter Visser

<p>The European Space Agency (ESA) Swarm mission was launched in November 2013 and consists of three identical satellites flying in near-polar orbits. One satellite is flying at about 515 km, while the other two satellites are flying side-by-side at lower altitudes, starting at 480 km altitude and slowly descending due to atmospheric drag to their current 445 km altitude. This coverage of altitudes, together with the satellite payload that includes an accelerometer and GPS receiver, makes the mission particularly suited for atmospheric density retrieval. Unfortunately, the Swarm accelerometers suffer from several anomalies which limits their usefulness for density retrieval. Currently, only accelerometer observations from one of the lower flying satellites (Swarm-C) can be used to generate high-resolution thermospheric densities. However, all satellites deliver high-quality GPS data and an alternative processing strategy has been developed to derive thermospheric densities from these observations as well.</p><p>This presentation describes the processing strategy that is used to derive thermospheric densities from the Swarm accelerometer and GPS observations and presents the latest results. The relatively smooth GPS-derived densities have a temporal resolution of about 20 minutes, and show variations due to solar and geomagnetic activity, as well as seasonal, latitudinal and diurnal variation. For analysis of higher-resolution phenomena, only the accelerometer-derived densities can be used. All Swarm thermospheric densities are available for users at the dedicated ESA Swarm website (ftp://swarm-diss.eo.esa.int), as well as at our thermospheric density database (http://thermosphere.tudelft.nl). This database also includes thermospheric densities for the CHAMP, GRACE and GOCE satellites. For future work, it is planned to further improve the Swarm densities, especially for low solar activity conditions, by including a more sophisticated radiation pressure modelling of the Swarm satellites. In addition, it is planned to extend our database with thermospheric densities for the GRACE-FO mission.</p>


2021 ◽  
Vol 13 (18) ◽  
pp. 3769
Author(s):  
Sumon Kamal ◽  
Norbert Jakowski ◽  
Mohammed Mainul Hoque ◽  
Jens Wickert

Under certain conditions, the ionization of the E layer can dominate over that of the F2 layer. This phenomenon is called the E layer dominated ionosphere (ELDI) and occurs mainly in the auroral regions. In the present work, we model the variation of the ELDI for the Northern and Southern Hemispheres. Our proposed Neustrelitz ELDI Event Model (NEEM) is an empirical, climatological model that describes ELDI characteristics by means of four submodels for selected model observables, considering the dependencies on appropriate model drivers. The observables include the occurrence probability of ELDI events and typical E layer parameters that are important to describe the propagation medium for High Frequency (HF) radio waves. The model drivers are the geomagnetic latitude, local time, day of year, solar activity and the convection electric field. During our investigation, we found clear trends for the model observables depending on the drivers, which can be well represented by parametric functions. In this regard, the submodel NEEM-N characterizes the peak electron density NmE of the E layer, while the submodels NEEM-H and NEEM-W describe the corresponding peak height hmE and the vertical width wvE of the E layer electron density profile, respectively. Furthermore, the submodel NEEM-P specifies the ELDI occurrence probability %ELDI. The dataset underlying our studies contains more than two million vertical electron density profiles covering a period of almost 13 years. These profiles were derived from ionospheric GPS radio occultation observations on board the six COSMIC/FORMOSAT-3 satellites (Constellation Observing System for Meteorology, Ionosphere and Climate/Formosa Satellite Mission 3). We divided the dataset into a modeling dataset for determining the model coefficients and a test dataset for subsequent model validation. The normalized root mean square deviation (NRMS) between the original and the predicted model observables yields similar values across both datasets and both hemispheres. For NEEM-N, we obtain an NRMS varying between 36.1% and 47.1% and for NEEM-H, between 6.1% and 6.3%. In the case of NEEM-W, the NRMS varies between 38.5% and 41.1%, while it varies between 56.5% and 60.3% for NEEM-P. In summary, the proposed NEEM utilizes primary relationships with geophysical and solar wind observables, which are useful for describing ELDI occurrences and the associated changes of the E layer properties. In this manner, the NEEM paves the way for future prediction of the ELDI and of its characteristics in technical applications, especially from the fields of telecommunications and navigation.


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