remote sensing
Article Co-Seismic Magnetic Field Perturbations Detected by Swarm Three-Satellite Constellation
1,2 2 1,3,4, 2, Dedalo Marchetti , Angelo De Santis , Shuanggen Jin *, Saioa A. Campuzano †, Gianfranco Cianchini 2 and Alessandro Piscini 2 1 School of Remote Sensing and Geomatics Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China; [email protected] 2 Istituto Nazionale di Geofisica e Vulcanologia, Via di Vigna Murata, 605, 00143 Rome, Italy; [email protected] (A.D.S); [email protected] (S.A.C.); [email protected] (G.C.); [email protected] (A.P.) 3 Jiangsu Engineering Center for Collaborative Navigation/Positioning and Smart Applications, Nanjing 210044, China 4 Shanghai Astronomical Observatory, Chinese Academy of Sciences, Shanghai 200030, China * Correspondence: [email protected] Now at Instituto de Geociencias IGEO (CSIC-UCM), 28040 Madrid, Spain. † Received: 14 January 2020; Accepted: 1 April 2020; Published: 5 April 2020
Abstract: The first 5.3 years of magnetic data from three Swarm satellites have been systematically analyzed, and possible co-seismic magnetic disturbances in the ionosphere were investigated just a few minutes after the occurrence of large earthquakes. We preferred to limit the investigation to a subset of earthquakes selected in function of depth and magnitude. After a systematic inspection of the available data around (in time and space) the seismic events, we found 12 Swarm satellite tracks with co-seismic disturbances possibly produced by ten earthquakes from Mw5.6 to Mw6.9. The distance of the satellite to the earthquake epicenter corresponds to the measured distance-time arrival of the disturbance from the surface to the ionosphere, confirming that the identified disturbances are most likely produced by the seismic events. Secondly, we found a good agreement with a model that combined a propagation of the disturbance to the F2 ionospheric layer with an acoustic gravity wave at a velocity of about (2.2 0.3) km/s and a second faster phenomenon that transmits the disturbance ± from F2 layer to the Swarm satellite with a velocity of about (16 3) km/s as an electromagnetic ± scattering propagation.
Keywords: geomagnetic field; co-seismic magnetic disturbance; Swarm satellites; earthquakes; gravity waves
1. Introduction This paper aimed to search for perturbations of the geomagnetic field in the ionosphere possibly produced by the occurrence of an earthquake in the lithosphere. The possibility that the ionosphere could be perturbed just a few minutes after the occurrence of a medium (Mw6+) and large (Mw7+) earthquakes is well known. For example, Yeh and Liu, 1974 [1] presented a model for the generation, propagation and response of the ionosphere to acoustic gravity waves. They also provided experimental data by supporting their model. Yamamoto, 1982 [2] theorized a model to describe the acoustic gravity waves induced by submarine earthquakes. Submarine earthquakes deserve special attention due to their potential to generate tsunamis. Lognonne et al., 2006 [3] observed the impact of the acoustic waves by the Global Positioning System (GPS) network 660–670 s (~11 min) after the arrival time of Rayleigh waves at the ground for the Mw7.9 November 3rd, 2002, Alaska earthquake. Hao et al., 2012 [4] reported not only ionospheric Doppler caused by the Mw9.0 Tohoku 2011 earthquake, but
Remote Sens. 2020, 12, 1166; doi:10.3390/rs12071166 www.mdpi.com/journal/remotesensing Remote Sens. 2020, 12, 1166 2 of 21 even geomagnetic disturbances from three different ground observatories. They carefully checked that the disturbances recorded on the ground were not caused by the ground shake due to the earthquake but as a magnetic effect. Jin et al., 2015 [5] presented a general review about the acoustic gravity waves produced by earthquakes and gravity waves generated by tsunamis, in particular focusing on the alteration of plasma density and velocity in ionosphere retrievable by the Global Navigation Satellite System (GNSS) global network sensors. Furthermore, they presented also a detailed analysis of the Mw7.8 Wenchuan 2008 and Mw9.0 Tohoku 2011 earthquakes. Many authors [5–9] analyzed the Total Electron Content (TEC) variations from ground GNSS receivers and Global Ionospheric Map (GIM) and detected the impact of the acoustic gravity wave in the ionosphere associated with the occurrence of earthquakes. The analysis of TEC data has also shown to be a useful tool to detect the main earthquake parameters (epicentre and magnitude) using fast analysis techniques [10]. Rapoport et al., 2004 [11] proposed the acoustic gravity waves as a possible mechanism to explain disturbances prior to the occurrence of the earthquakes. They conducted three-dimensional (3D) simulations of the atmosphere and the ionosphere and found perturbations before some earthquakes. They also provided a possible explanation for the reason why the Outgoing Long-wave Radiation (OLR) anomalies generally are not found directly above the epicentre. As the authors suggested, this is only one of the various mechanisms for a possible pre-seismic alteration of the ionosphere. Other mechanisms are the possible electromagnetic coupling (e.g., [12,13]) or a more complex chain of physical, chemical and electromagnetic processes such as the one described by [14]. The aim of this paper is to study the potentiality of using magnetic data from space to identify co-seismic magnetic disturbances. In particular, the analysis will be focused in this investigation on the direction and value of the geomagnetic field as measured by satellites, with particular attention in the frequency band between 0.25 Hz and 0.50 Hz. The measurement of the geomagnetic field from space implies that the satellite is not necessarily close to the epicentral zone during and after the occurrence of the seismic event. Swarm satellites constellation has the advantage to be successful in orbit for more than five years and that as a constellation, it increases the probability of detection. Although the constellation is composed by three identical satellites, the probability of detection of the possible co-seismic signal is increased by a factor of about two as two of three satellites (Alpha and Charlie) fly close each other. In Section2, the earthquake catalogue, Swarm magnetic dataset and data analysis methods are presented. The results of the automatic analysis of Swarm magnetic data are reported in Section3, and a possible propagation model is discussed in Section4. Some conclusions are finally given in Section5.
2. Datasets and Methods of Analysis In this section, the used datasets and methodology are presented. In particular, in Section 2.1, we present the earthquake catalogue and the criteria to select the seismic events; Section 2.2 presents the magnetic satellite data of the European Space Agency (ESA) Swarm mission. Finally, Section 2.3 details the methods of analysis.
2.1. Earthquake Catalogue The seismic events were selected from the United States Geological Survey (USGS) catalogue. From the catalogue, all recorded events from 25 November 2013 to 12 April 2019 with a magnitude equal to or greater than 5.5 were downloaded and represented with a black star or dot in Figure1 according to their geographical distribution (Figure1a) and the magnitude /depth distribution (Figure1b). Although some authors also included deep earthquakes in ionospheric disturbance investigations [15,16], we prefer to exclude them, as we consider the possibility that deep earthquakes could affect the ionosphere to be lower. To achieve this selection, all Mw5.5+ events up to 20 km depth were selected and for more in-depth events, a selection based on a higher magnitude and depth was applied. In particular, a linear interpolation was applied from Mw5.5 at 20 km and Mw7.0 at 150 km depth. This choice is a compromise to exclude the deeper earthquakes but not the strongest and deepest events that could Remote Sens. 2020, 12, 1166 3 of 21 Remote Sens. 2020, 12, x FOR PEER REVIEW 3 of 20 producedeepest a disturbanceevents that could in the produce ionosphere a disturbance because of in their the significantionosphere released because energy.of their Thesignificant number of thereleased selected energy. events The was number 1830 of out the of selected 2437 downloaded events was earthquakes,1830 out of 2437 represented downloaded by earthquakes, a red star/dot in Figurerepresented1. In particular,by a red star/dot in Figure in Figure1b it is1. possibleIn particular, to note in Figure the exclusion 1b it is possible of the deepestto note the events. exclusion The selectedof the earthquakesdeepest events. are The a sub-setselected inearthquakes which it is are more a sub- reliableset in which to search it is more for e reliableffects induced to search in for the ionosphere,effects induced but future in the works ionosphere, can also but investigate future works other can events also investigate or subsets. other events or subsets.
FigureFigure 1. Earthquakes 1. Earthquakes extracted extracted from from USGS USGS catalogue catalogu Mw5.5e Mw5.5++ from from 2013-11-25 2013-11-25 to 2019-04-12to 2019-04-12 (black) (black) and thoseand selected those forselected the analysis for the (red). analysis (a) Geographical (red). (a) distribution,Geographical ( b)distribution, earthquakes ( magnitudeb) earthquakes/depth plot.magnitude/depth The blue line showsplot. The the blue limit line criterion shows the used limit to selectcriterion the used earthquakes: to select the for earthquakes: instance, Mw5.5 for earthquakesinstance, Mw5.5 have a earthquakes depth threshold have of a 20depth km threshold as well as of Mw7.0 20 km of as 150 well km as and Mw7.0 Mw of= 1508.0 aroundkm and 240Mw km. = 8.0 around 240 km. 2.2. Swarm Satellite Magnetic Data 2.2.In Swarm this paper, Satellite the Magnetic data from Data the ESA Swarm mission have been investigated. The main goal of the missionIn this was paper, to measure the data and from monitor the ESA the Swarm Earth’s miss magneticion have field been with investigated. global coverage The main and goal better of understandthe mission the was electromagnetic to measure and phenomena monitor the on Earth’s our planet magnetic [17 ].field Swarm with global is a three-identical coverage and satellitebetter constellationunderstand successfully the electromagnetic launched phenomena on 22 November on our 2013. planet The [17]. mission Swarm is stillis a three-identical in orbit, and the satellite present objectiveconstellation is to extend successfully the mission launched for an on entire 22 November solar cycle 2013. of The 11 years. mission Most is still of thein orbit, instruments and the present continue to workobjective in nominal is to extend conditions. the mission Currently, for an entire more sola thanr cycle five of years 11 years. of data Most are of available.the instruments continue toThe work three in nominal satellites conditions. follow quasi-polar Currently, orbits:more than two five of them years (called of data Alpha are available. and Charlie) fly close to each otherThe at three a lower satellites orbit follow (around quasi-polar 450 km) and orbits: the two other of one,them called (called Bravo, Alpha currently and Charlie) has afly separation close to each other at a lower orbit (around 450 km) and the other one, called Bravo, currently has a separation of about 90◦ longitude, and it is placed at a higher orbit, around 510 km. In the first months of the mission,of about all 90° the longitude, satellites orbited and it is close placed to eachat a higher other. orbit, around 510 km. In the first months of the mission,Each satellite all the satellites is equipped orbited with close the to each following other. payloads: Vector Field Magnetometer (VFM), Each satellite is equipped with the following payloads: Vector Field Magnetometer (VFM), Absolute Scalar Magnetometer (ASM), electric field instrument (EFI), accelerometers, GNSS receivers Absolute Scalar Magnetometer (ASM), electric field instrument (EFI), accelerometers, GNSS receivers and laser retroreflectors. The VFM and ASM measure the orientation and intensity of the magnetic and laser retroreflectors. The VFM and ASM measure the orientation and intensity of the magnetic field. These sensors are placed on a 4-m length boom to avoid possible interferences with the satellite field. These sensors are placed on a 4-m length boom to avoid possible interferences with the satellite platform. The VFM sensor, placed half-way along the boom, is a fluxgate magnetometer with three-axis platform. The VFM sensor, placed half-way along the boom, is a fluxgate magnetometer with three- compactaxis compact spherical spherical coil with coil with a three-axis a three-axis compact compac detectort detector coil coil inside. inside. TheThe magnetic field field intensity intensity calibrationcalibration of theof the VFM VFM is is based based on on the the data data acquired acquired byby thethe ASMASM instrument placed placed at at the the end end of of the the boom.boom. For For the the Charlie Charlie satellite, satellite, the the calibration calibration isis setset onon the data of Alpha Alpha ASM, ASM, as as its its ASM ASM has has not not functionedfunctioned since since November November 2013. 2013. The The orientation orientation ofof thethe VFM was precisely precisely monitored monitored with with three three star-trackerstar-tracker cameras cameras placed placed on on the the same same optical optical bank bank of of thethe magnetometer.magnetometer. TheThe Swarm Swarm mission mission has has already already provided provided vastvast results;results; among them, a a map map of of the the lithospheric lithospheric magneticmagnetic field field with with a resolution a resolution up up to 250to 250 km km [18 [18]] and and the the oceanic oceanic tidal tidal eff ecteffect on on geomagnetic geomagnetic field field and electromagneticand electromagnetic induction induction generated genera byted oceanic by oceanic circulation circulation (e.g., (e.g., [19– [19–21]).21]). Furthermore, Furthermore, some some of of the authorsthe authors of this paperof thisfound paper afound series a of series anomalies of anomal in Swarmies in Swarm magnetic magnetic field and field electron and electron density density data that coulddata be that related could to be the related preparation to the phasespreparation of some phases earthquakes of some aroundearthquakes the worldaround (e.g., the Mw7.8world (e.g., Nepal 2015Mw7.8 [22], Mw8.2Nepal 2015 Mexico [22], 2017 Mw8.2 [23], Mexico 2018, Mw6.5 2017 [23], Italy 2018, 2016 Mw6.5 [24], Mw7.3 Italy 2016 Iran [24], 2017 Mw7.3 [25], Mw7.5 Iran 2017 Indonesia [25], 2018Mw7.5 [26]). Indonesia A recent paper 2018 [26]). by De A Santis recent et paper al., 2019 by De [27 Santis] provided et al., for 2019 the [27] first provided time a worldwide for the first statistical time a correlation of Swarm electron density and magnetic anomalies with earthquake occurrences, finding
Remote Sens. 2020, 12, 1166 4 of 21 some distinct concentrations of anomalies that preceded the earthquakes from some days to several months; additionally, a linear dependency was established between the logarithm of the anticipation time of the anomaly and the earthquake magnitude, confirming for satellite data the empirical Rikitake law [28], which was already introduced for ground precursors. The Swarm magnetic data have been downloaded from the free accessible FTP repository (swarm-diss.eo.esa.int) in Level 1B as CDF files with the filename SW_OPER_MAGx_LR_1B_[ ... ], where x stands for A, B or C satellite and the filename is completed with the starting and ending timestamp of the file and the data version (408 for most of this work and 505 for the most recent data). MAG is the label that identifies the magnetic product and LR stands for Low Resolution (1 Hz) that is a product re-sampled from the original one (HR, i.e., High Resolution: 50 Hz) at the GPS seconds.
2.3. Methods to Analyze the Magnetic Satellite Data A series of MATLAB® routines have been developed to analyze the Swarm Magnetic data. The first script reads the earthquake catalogue and selects the events in agreement with the magnitude–depth requirements described in Section 2.1 (all earthquakes with Mw 5.5 and depth according to a linearly ≥ varying threshold from 20 km depth for Mw = 5.5 and Mw = 7.0 at 150 km depth). For each event, the algorithm selects the magnetic satellite data on the same date. The polar regions above a 70◦ geographical latitude are cut, as they are not suitable for this study due to the typical perturbation of the auroral activity. The goal of this work was to analyze the anomalous magnetic activity associated with earthquakes; thus, other magnetic perturbations, such as the geomagnetic storms, must first be rejected. After that, the script calculates the spatial distance of each sample from the epicentre and the time difference between the acquisition time and the earthquake origin time. If there are some samples close in space-time to the seismic event (distance 150 km and time difference from 10 min before ≤ until 20 min after the earthquake), the script selects and runs an automatic analysis of the close track. Two types of automatic analyses have been performed: the first one is called Method 1, and it is the same proposed in previous works on Swarm data related to earthquakes (e.g., [22,24]. This technique consists of computing the first derivative of the data along the track approximated as the first difference divided for the time interval between two consecutive samples. After this step, a cubic spline is removed and the residuals of X, Y, Z (geomagnetic components) and F (intensity) are plotted with a fixed maximum range of 1 nT/s. ± The second method (so-called Method 2) has been developed to avoid a possible over-fitting problem of the first method, i.e., that the spline could remove the eventual perturbation induced by the supposed gravity wave. It consists of the subtraction of the International Geomagnetic Reference Field (IGRF-12) model [29] from the original data and the plotting of the residuals in X, Y, Z and F. The IGRF-12 is a global Earth’s magnetic field model, which is expected to be sufficient to highlight the studied disturbances. A five-degree polynomial has been further applied to remove the residual trend of each track. The output figures of both methods are presented in the Supplementary Materials. Each figure presents a map of the geographical region crossed by the satellite, the projection of the satellite track on the ground (brown for normal conditions and red for some abnormal conditions on the satellite) and the earthquake epicenter (green star). The title of the figure provides the satellites, the time in UTC and Local Time and the geomagnetic indices Dst and ap during the acquisition time. The residuals of X, Y, Z and F are reported together with the Fast Fourier Transform analysis of the signal that helps to select the best cut-off frequency for the following signal processing (for the second method, the mean of the signal is subtracted before calculating the FFT). The figures are grouped in tables that refer to each seismic event. All the satellite data of the selected track are stored in a text file for further analysis. The produced material is visually investigated and the tracks that present some possible features linkable to the seismic events are then re-analyzed and plotted again. For this final analysis (presented in Figures 3–14), only the Y component is considered: after the subtraction of IGRF-12 model, a high pass filter at 0.25 Hz Remote Sens. 2020, 12, 1166 5 of 21
Remote Sens. 2020, 12, x FOR PEER REVIEW 5 of 20 was applied and both quantities were then plotted. The frequency cut-off was chosen after multiple testspass as filter the bestat 0.25 value Hz towas extract applied the and anomalous both quanti signalties possibly were then related plotted. to theThe seismic frequency event. cut-off Taking was into accountchosen thatafter the multiple sampling tests rate as ofthe the best data value was to 1 Hz,extract the the available anomalous band signal was 0.25 possibly Hz–0.50 related Hz (following to the seismic event. Taking into account that the sampling rate of the data was 1 Hz, the available band Nyquist theorem). was 0.25 Hz–0.50 Hz (following Nyquist theorem). 3. Results of the Analysis 3. Results of the Analysis From the launch of the mission on November 22nd, 2013 until April 2019, the Swarm satellite data From the launch of the mission on November 22nd, 2013 until April 2019, the Swarm satellite have been analyzed to search when one or more satellites passed above the epicentral area during an data have been analyzed to search when one or more satellites passed above the epicentral area earthquake occurrence. To be conservative, a simultaneous passage was defined by a circular area of during an earthquake occurrence. To be conservative, a simultaneous passage was defined by a 150 km around the epicentre and a time window that spanned 10 min before the event until 20 min circular area of 150 km around the epicentre and a time window that spanned 10 min before the event after.until With20 min such after. criteria, With 37such satellite criteria, passages 37 satellit (tracks)e passages were selected.(tracks) were For eachselected. case, For method each case, 1 and 2 weremethod applied, 1 and searching 2 were applied, for possible searching “interesting” for possible features “interesting” in the residualfeatures in of the at leastresidual one of method. at least We finallyone method. noticed We that finally even ifnoticed the algorithm that even selected if the algo therithm space-time selected tracks the space-time closer to thetracks epicenter, closer to in the some cases,epicenter, the satellites in some passedcases, the too satellites early or passed too late too above early theor too epicentral late above area, the losingepicentral the area, chance losing to detect the a co-seismicchance to signal. detect Aftera co-seismic visually signal. inspecting After the visually residual inspecting plots, 12 tracksthe residual were considered plots, 12 tracks the most were likely candidateconsidered containing the most alikely co-seismic candidate effect. containing Figure2 areports co-seismic the distributioneffect. Figure map 2 reports of the the earthquakes distribution and themap ionospheric of the earthquakes disturbances and the possibly ionospheric associated disturbanc withes the possibly seismic associated events. with the seismic events.
FigureFigure 2. 2.Geographical Geographical distributiondistribution ofof thethe earthquakesearthquakes (red(red star) and positions of the satellites satellites when when an ionospherican ionospheric disturbance disturbance was was detected detected (filled (filled circleby circleby a dia differentfferent colour colour for for each each satellite). satellite).
TableTable1 reports1 reports the the list list of of the the earthquakesearthquakes that present a a possible possible magnetic magnetic disturbance disturbance in inthe the ionosphereionosphere withwith thethe SwarmSwarm satellitesatellite characteristicscharacteristics in in the the moment moment of of disturbance disturbance detection. detection. The The measuredmeasured time time is is that that after after the the origin origin time time of theof earthquakethe earthquake in which in which the anomalythe anomaly starts starts to be to detected be bydetected the Swarm by the satellite. Swarm Thesatellite. table The also table reports also report the heights the inheight km ofin thekm of ionospheric the ionospheric F2 electron F2 electron density peakdensity (hmF2) peak estimated (hmF2) estimated by the IRI-2016 by the IRI-2016 model [model30] and [30] the and air temperaturethe air temperature at 2 m at retrieved 2 m retrieved from the Europeanfrom the CentreEuropean for Medium-rangeCentre for Medium-range Weather Forecast Weather (ECMWF) Forecast ERA-Interim(ECMWF) ERA-Interim archive, which archive, will be usedwhich for will the be discussion used for the and discussion interpretation and interpretation of the results. of the results.
Table 1. List of the earthquakes that created a potential magnetic disturbance in the ionosphere as detected from the Swarm satellite. The orbital characteristics are reported (satellite, direction of the semi-orbit: D for downward orbit, U for upward orbit, altitude, latitude and longitude) in the moment of disturbance detection. The height of the F2 ionospheric layer (hmF2) and the surface air temperature are also provided.
Remote Sens. 2020, 12, 1166 6 of 21
Table 1. List of the earthquakes that created a potential magnetic disturbance in the ionosphere as detected from the Swarm satellite. The orbital characteristics are reported (satellite, direction of the semi-orbit: D for downward orbit, U for upward orbit, altitude, latitude and longitude) in the moment of disturbance detection. The height of the F2 ionospheric layer (hmF2) and the surface air temperature are also provided.
Relative Earthquake Characteristics Satellite Characteristics Characteristics hmF2 [km] U / Lat D SAT Mag Air Temperature [K] Long Lat Sat Long Sat Depth [km] Altitude [km] Year-Month-Day Total Distance [km] Hour-Minute-Second Measured Time [min] Lorizontal Distance [km]
BD 500.2 10.003 74.187 292 454 2687 2733.2 5.151 2014-02-18 23:35:58 14.165 75.6 5.9 57.0 − − − CD 499.5 11.164 74.514 292 454 2814 2858.0 6.184 − 2014-10-22 00:15:17 27.416 128.553 5.8 43.0 AU 462.6 48.228 129.711 292 254 2312 2357.8 4.617 2015-11-11 02:46:19 29.51 72.058 6.9 10.0 AU 463.7 39.037 71.541 289 368 1059 1156.1 3.050 − − − − 2016-04-17 07:31:00 23.495 174.247 5.7 10.0 CD 449.5 27.676 174.798 296 268 5680 5697.8 6.650 − − − 2016-04-29 01:33:38 10.275 103.736 6.6 10.0 CD 444.9 51.651 103.638 305 321 4593 4614.5 8.050 − − 2016-06-15 06:58:27 62.366 166.58 5.7 10.0 BD 518.7 26.200 168.448 266 310 4017 4050.3 6.550 − − 2017-01-16 12:42:10 3.317 98.47 5.6 6.0 A D 451.1 0.973 97.400 297 349 4907 4927.7 6.517 − 2018-07-17 07:02:53 11.594 166.432 6.0 38.0 CD 448.0 8.287 165.250 301 271 3891 3916.7 8.683 − − 2019-04-05 16:14:16 55.932 27.846 6.4 58.4 BU 510.0 30.412 28.208 274 231 2833 2878.5 3.517 − − − − AU 470.0 53.197 73.643 290 288 2159 2209.6 5.517 2019-04-07 10:52:41 33.764 72.521 5.6 10.0 − − − − CU 470.0 52.592 72.142 290 288 1884 2090.0 5.567 − −
The Swarm magnetic data during the earthquake occurrence are represented following the same order of Table1, i.e., a chronological one, from Figures3–13. Each figure is horizontally aligned with the origin time of the earthquake. In the upper part is shown in red the residual of the Y component of the magnetic field with respect to the IGRF-12 model. The Y component was selected as it is the most sensible for the internal perturbations ([22,31]). In the lower graph, a 0.25 Hz high-pass filter was applied, and the filtered data are shown in blue. Here, we did not subtract any polynomial, as the filter was sufficient to remove the residual trend. A black vertical line underlines the position where the satellite crosses the earthquake latitude if it is after the earthquake occurrence. An orange line represents the latitude of the satellite. Note that only the data inside 70 and +70 geographical − ◦ ◦ latitude are shown. More details are provided in the Supplementary Materials, where Figures S1–S10 show the residuals of the other components as well as the total intensity of the magnetic field, as deduced using method 1 and method 2. Figure S11 also shows an example of a track without any evidence of possible co-seismic magnetic disturbance. The reasons for the lack of disturbance in the latter case could be several: the earthquake happened in the Atlantic ocean ridge and the ocean water depth at the epicentre is of several kilometres (about 3.4 km), thus possibly attenuating the mechanical effect (also considering the low magnitude of the event: Mw 5.5); another reason could be an intrinsic disturbance in the magnetic signal all over the track that could cover the detection of any small co-seismic effect. On the other hand, in the Figures S1–S10, the magnetic disturbance cannot be explainable merely by geomagnetic activity, which was low at the acquisition time; nevertheless, it could be induced by some other geophysical source (such as electric and magnetic fields produced by ocean currents—Grayver et al., 2016—or tectonic stress along the ocean drift). Remote Sens. 2020, 12, x FOR PEER REVIEW 7 of 20 Remote Sens. 2020, 12, x FOR PEER REVIEW 7 of 20 we also present in the Appendix an automatic approach that is totally objective and practically we also present in the Appendix an automatic approach that is totally objective and practically confirms our results. confirmsFor theour earthquake results. that occurred on 2014-02-18, only the tracks of Bravo and Charlie (Figure 3 For the earthquake that occurred on 2014-02-18, only the tracks of Bravo and Charlie (Figure 3 and Figure 4) are provided as Swarm Alpha was not in nominal conditions during the passage over and Figure 4) are provided as Swarm Alpha was not in nominal conditions during the passage over the epicentral area. Most of the data present a discrepancy between ASM and VFM measurements the epicentral area. Most of the data present a discrepancy between ASM and VFM measurements (Flag_F = 16), and the attitude information was interpolated with the nearest points for lack of data (Flag_F = 16), and the attitude information was interpolated with the nearest points for lack of data from two or all three star-cameras. These conditions were probably due to the early stage of the from two or all three star-cameras. These conditions were probably due to the early stage of the mission that we analyzed. mission that we analyzed. An earthquake happened offshore Chile on 2015-11-11 at a depth of 10 km between the Nazca and South-AmericanAn earthquake happened plates. In thisoffshore case, Chilea perturbati on 2015-11-11on was visibleat a depth just northof 10 kmof the between epicentre the and Nazca we and South-American plates. In this case, a perturbation was visible just north of the epicentre and we cannot exclude that this could be an electromagnetic phenomenon coming directly from the fault. cannot exclude that this could be an electromagnetic phenomenon coming directly from the fault. There was a certain symmetry of the signal with respect to the epicentre latitude. The ionospheric RemoteThere Sens. was2020 a, 12certain, 1166 symmetry of the signal with respect to the epicentre latitude. The ionospheric7 of 21 disturbance was possibly associated with the high magnitude earthquake (Mw 6.9) considered in this disturbance was possibly associated with the high magnitude earthquake (Mw 6.9) considered in this case (Figure 6). case (Figure 6).
FigureFigure 3. 3.Residual Residual of of the the Y Y component component ofof the Swarm Brav Bravoo magnetic magnetic field field after after the the occurrence occurrence of the of the Figure 3. Residual of the Y component of the Swarm Bravo magnetic field after the occurrence of the MwMw 5.9 5.9 2014-02-18 2014-02-18 earthquake. earthquake. The The vertical vertical black black line line in the in thelower lower plot plotrepresents represents the point the where point wherethe Mw 5.9 2014-02-18 earthquake. The vertical black line in the lower plot represents the point where the thesatellite satellite crosses crosses the the earthquake earthquake latitude. latitude. The The vert verticalical green green line line is the is the candidate candidate point point where where the the satellite crosses the earthquake latitude. The vertical green line is the candidate point where the earthquake-inducedearthquake-induced phenomena phenomena areare supposedsupposed to star start.t. A A zoom zoom around around the the selected selected anomalies anomalies is is earthquake-induced phenomena are supposed to start. A zoom around the selected anomalies is provided,provided, where where it it is is visible visible that that the the anomalyanomaly has be beenen preceded preceded by by a afew few different different samples samples circled circled in in provided, where it is visible that the anomaly has been preceded by a few different samples circled in red, which suggests this point as the possible arrival of a co-seismic signal at the satellite position. In red,red, which which suggests suggests this this point point as as the the possible possible arrival arrival of of a a co-seismic co-seismic signal signal at at the the satellite satelliteposition. position. In the the Supplementary Materials, more details and the other available Swarm magnetic data are Supplementarythe Supplementary Materials, Materials, more detailsmore details and the and other the available other available Swarm magneticSwarm magnetic data are representeddata are represented (Figure S1). (Figurerepresented S1). (Figure S1).
Figure 4. Residual of the Y component of the Swarm Charlie magnetic field after the occurrence of the Mw 5.9 2014-02-18 earthquake. The vertical black line in the lower plot represents the point where the satellite crosses the earthquake latitude. The vertical green line is the candidate point where the earthquake-induced phenomena are supposed to start. This anomaly has been selected as it is the wider after the earthquake occurrence and it is the corresponding anomaly of the previous track (acquired after few seconds). In the Supplementary Materials, more details and the other available Swarm magnetic data are represented (Figure S1). Remote Sens. 2020, 12, x FOR PEER REVIEW 8 of 20 Remote Sens. 2020, 12, x FOR PEER REVIEW 8 of 20 Figure 4. Residual of the Y component of the Swarm Charlie magnetic field after the occurrence of the FigureMw 5.9 4. 2014-02-18 Residual of earthquake. the Y component The vertical of the black Swarm line Char in thelie lowermagnetic plot field represents after the the occurrence point where of thethe Mwsatellite 5.9 2014-02-18 crosses the earthquake. earthquake The latitude. vertical The black vert lineical in greenthe lower line plot is the represents candidate the point point where thethe satelliteearthquake-induced crosses the earthquakephenomena latitude. are supposed The vert to icalstart. green This lineanomaly is the has candidate been selected point whereas it is thethe earthquake-inducedwider after the earthquake phenomena occurrence are supposed and it isto thestart. corresponding This anomaly anomaly has been of selected the previous as it is track the wider after the earthquake occurrence and it is the corresponding anomaly of the previous track Remote Sens.(acquired2020, 12 after, 1166 few seconds). In the Supplementary Materials, more details and the other available 8 of 21 (acquiredSwarm magnetic after few data seconds). are represented In the Supplementary (Figure S1). Materials, more details and the other available Swarm magnetic data are represented (Figure S1).
Figure 5. Residual of the Y component of the Swarm Alpha magnetic field after the occurrence of the FigureFigureMw 5.5.8 Residual5. 2014-10-22 Residual of of theearthquake. the Y componentY component The vertical of of the the Swarm greenSwarm Alphalin Alphe is the magnetica magnetic candidate field field point after after where the the occurrence occurrence the earthquake- of of the the Mw 5.8Mwinduced 2014-10-22 5.8 2014-10-22 phenomena earthquake. earthquake. are Thesupposed vertical The tovertical greenstart. We linegreen selected is lin thee candidateis thisthe candidateanomaly point be point wherecause where theit is earthquake-induced the the first earthquake- after the phenomenainducedearthquake phenomena are occurred, supposed are while tosupposed start. those We o toccurredselected start. afterWe this selected 7 min anomaly are this localized becauseanomaly atit behigh iscause the latitudes, first it is afterthe and first the thus earthquakeafter more the occurred,earthquakelikely due while tooccurred, thosemagnetic occurred while auroral those after activity. occurred 7 min The are after localizeddata 7 min after are at +70° localized high of latitudes, geographical at high and latitudes, thuslatitude more and are thus likely cut. more The due to likely due to magnetic auroral activity. The data after +70° of geographical latitude are cut. The magneticsatellite auroral passed activity.just before The the dataearthquake after + over70◦ of the geographical latitude of the latitude epicentre. are After cut. little The satellitemore than passed 10 justsatellitemin, before the passed thesatellite earthquake just overpassed before over the the theearthquake 70° latitude north overgeographic of the the epicentre. latitudeal latitude, of After the and epicentre. little thus, more the After thandata little are 10 min, notmore shown. the than satellite 10In min, the satellite overpassed the 70° north geographical latitude, and thus, the data are not shown. In overpassedthe Supplementary the 70◦ north Materials, geographical more details latitude, and and othe thus,r available the data Swarm are not magnetic shown. data In the are Supplementary represented Materials,the(Figure Supplementary moreS2). details Materials, and other more available details Swarmand othe magneticr available data Swarm are magnetic represented data (Figure are represented S2). (Figure S2).
FigureFigure 6. Residual6. Residual of of the the Y Y component component ofof thethe SwarmSwarm Alph Alphaa magnetic magnetic field field after after the the occurrence occurrence of the of the MwFigureMw 6.9 6.9 2015-11-11 6. 2015-11-11 Residual earthquake. ofearthquake. the Y component The vertical vertical of the black blackSwarm line line Alph in inthea the magneticlower lower plot fieldplot represents after represents the the occurrence point the pointwhere of wherethethe theMwsatellite satellite 6.9 2015-11-11 crosses crosses the theearthquake. earthquake earthquake The latitude. latitude.vertical The black The vert line verticalical in greenthe green lower line line plot is isthe represents the candidate candidate the point point point where where thethe the earthquake-inducedsatelliteearthquake-induced crosses thephenomena earthquakephenomena latitude.areare supposed The vertto to start.ical start. Wegreen We selected line selected is this the thisanomaly candidate anomaly because point because itwhere is the it firstthe is the firstearthquake-inducedon on the the track track after after the thephenomena earthquake. earthquake. are Moreover, supposed Moreover, towe start. we no noticedticed We selectedthat that its itsshapethis shape anomaly is different is di becausefferent from fromit isthe the the other first other on the track after the earthquake. Moreover, we noticed that its shape is different from the other anomalies,anomalies, as as the the amplitude amplitude is is almost almost constantconstant (peak-to-peak(peak-to-peak about about 1nT) 1nT) during during its its duration duration (little (little anomalies, as the amplitude is almost constant (peak-to-peak about 1nT) during its duration (little more than 1 min), which is different from the other anomalies that increase, reach a maximum and then
decrease. In the Supplementary Materials, more details and the other available Swarm magnetic data are represented (Figure S3). Remote Sens. 2020, 12, x FOR PEER REVIEW 9 of 20
more than 1 min), which is different from the other anomalies that increase, reach a maximum and Remote Sens. 2020, 12, 1166 9 of 21 then decrease. In the Supplementary Materials, more details and the other available Swarm magnetic data are represented (Figure S3).
FigureFigure 7. 7.Residual Residual of of the the Y componentY component of of Swarm Swarm Charlie Charlie magnetic magnetic field field after after the the occurrence occurrence of of the the Mw 5.7Mw 2016-04-17 5.7 2016-04-17 earthquake. earthquake. The verticalThe vertical black black line li (atne the(at rightthe right of theof the lower lower graph, graph, about about 20 20 m m after after the earthquake) represents the point where the satellite crosses the earthquake latitude. The theafter earthquake) the earthquake) represents represents the point the wherepoint where the satellite the satellite crosses crosses the earthquake the earthquake latitude. latitude. The verticalThe vertical green line is the candidate point where the earthquake-induced phenomena are supposed to greenvertical line green is the line candidate is the candidate point where point thewhere earthquake-induced the earthquake-induced phenomena phenomena are are supposed supposed to to start. start. Additionally, a zoom of the track around the selected point is provided. In the selection, we take Additionally, a zoom of the track around the selected point is provided. In the selection, we take into into account that the disturbance between 0 and 1 min appears too early to be an acoustic gravity account that the disturbance between 0 and 1 min appears too early to be an acoustic gravity wave wave with respect to the earthquake origin time, while the selected one is more reliable. The with respect to the earthquake origin time, while the selected one is more reliable. The disturbance disturbance between 1 and 6 min seems to be characteristic of this orbit. In the Supplementary between 1 and 6 min seems to be characteristic of this orbit. In the Supplementary Materials, more Materials, more details and the other available Swarm magnetic data are represented (Figure S4). details and the other available Swarm magnetic data are represented (Figure S4).
FigureFigure 8. 8.Residual Residual ofof the Y Y component component of ofSwarm Swarm Bravo Bravo magnetic magnetic field fieldafter the after occurrence the occurrence of the Mw of the Mw5.7 5.7 2016-06-15 2016-06-15 earthquake. earthquake. The Thevertical vertical black black line in line the in lower the lower plot represents plot represents the point the where point wherethe thesatellite satellite crosses crosses the the earthquake earthquake latitude. latitude. The Thevertical vertical green green line is line the iscandidate the candidate point where point wherethe theearthquake-induced earthquake-induced phenomena phenomena are aresupposed supposed to start; to start; a zoom a zoom of the of the signal signal around around this this point point is is providedprovided because because the the high-latitude high-latitude disturbancesdisturbances incr increasedeased the the vertical vertical scale. scale. We We selected selected this this point point becausebecause the the signal signal after after this this point point presentspresents a behavi behavioror similar similar to to the the one one of ofFigure Figure 6 but6 but with with lower lower amplitude.amplitude. The The anomalies anomalies after after 14 14 minmin are probably due due to to the the south south auroral auroral magnetic magnetic activity. activity. About About 18 min after the earthquake, the satellite went below -70° geographical latitude, thus, the data are not 1818 min min after after the the earthquake, earthquake, the the satellite satellite wentwent belowbelow -70°70 geographicalgeographical latitude, latitude, thus, thus, the the data data are arenot not − ◦ shown. In the Supplementary Materials, more details and the other available Swarm magnetic data are
represented (Figure S6). Remote Sens. 2020, 12, x FOR PEER REVIEW 10 of 20 Remote Sens. 2020, 12, x FOR PEER REVIEW 10 of 20
Remote Sens.shown.2020 ,In12 ,the 1166 Supplementary Materials, more details and the other available Swarm magnetic data 10 of 21 shown. In the Supplementary Materials, more details and the other available Swarm magnetic data are represented (Figure S6). are represented (Figure S6).
Figure 9. Residual of the Y component of Swarm Alpha magnetic field after the occurrence of the Mw FigureFigure 9. 9.Residual Residual of of the the Y Y component component of Swarm Alpha Alpha ma magneticgnetic field field after after the the occurrence occurrence of the of theMw Mw 5.6 2017-01-16 earthquake. The vertical green line in the lower plot is the candidate point where the 5.65.6 2017-01-16 2017-01-16 earthquake. earthquake. TheThe verticalvertical green line line in in the the lower lower plot plot is isthe the candidate candidate point point where where the the earthquake-induced phenomena are supposed to start. We excluded the anomalies at the beginning earthquake-inducedearthquake-induced phenomena phenomena areare supposedsupposed to to star start.t. We We excluded excluded the the anomalies anomalies at atthe the beginning beginning of the track, which are too close to the earthquake (this could be due to the equatorial electrojet or of the track, which are too close to the earthquake (this could be due to the equatorial electrojet or of theother track, equatorial which electromagnetic are too close to phenomena). the earthquake The se (thislected could point be isdue the start to the of equatorialthe wider anomalies electrojet or other equatorial electromagnetic phenomena). The selected point is the start of the wider anomalies otherin the equatorial track. We electromagnetic noticed that its phenomena). duration is longer Theselected than other point selected is the anomalies. start of the The wider vertical anomalies black in in the track. We noticed that its duration is longer than other selected anomalies. The vertical black theline track. represents We noticed the thatpoint its where duration the issatellite longer crosses than other the earthquake selected anomalies. latitude. The verticalSupplementary black line line represents the point where the satellite crosses the earthquake latitude. The Supplementary representsMaterials the show point more where details the satelliteand the other crosses availa theble earthquake Swarm magnetic latitude. data The are Supplementary represented (Figure Materials Materials show more details and the other available Swarm magnetic data are represented (Figure showS7). more details and the other available Swarm magnetic data are represented (Figure S7). S7).
FigureFigure 10. 10.Residual Residual of of the the Y Y component component ofof SwarmSwarm Charlie magnetic magnetic field field after after the the occurrence occurrence of the ofthe Figure 10. Residual of the Y component of Swarm Charlie magnetic field after the occurrence of the Mw 6.0 2018-07-17 earthquake. The vertical black line in the lower plot represents the point where the MwMw 6.0 6.0 2018-07-17 2018-07-17 earthquake. earthquake. The The vertical vertical black black line line in the in thelower lower plot plotrepresents represents the point the where point wherethe satellite crosses the earthquake latitude. The vertical green line is the candidate point where the thesatellite satellite crosses crosses the the earthquake earthquake latitude. latitude. The The vert verticalical green green line line is the is the candidate candidate point point where where the the earthquake-induced phenomena are supposed to start. In this case, we excluded the anomalies closer earthquake-inducedearthquake-induced phenomena phenomena are are supposedsupposed to start. In In this this case, case, we we excluded excluded the the anomalies anomalies closer closer to the time of the earthquake occurrence (as in previous cases) and we selected the first anomaly after to theto the time time of of the the earthquake earthquake occurrence occurrence (as(as in previous previous cases) cases) and and we we selected selected the the first first anomaly anomaly after after earthquake. Other anomalies are present in the track, while the selected one seems to be symmetric earthquake.earthquake. Other Other anomalies anomalies areare presentpresent in the track, track, while while the the selected selected one one seems seems to tobe besymmetric symmetric with respect to the epicenter. In the Supplementary Materials, more details and the other available withwith respect respect to to the the epicenter. epicenter. In Inthe the SupplementarySupplementary Materials, Materials, more more details details and and the the other other available available Swarm magnetic data are represented (Figure S8). SwarmSwarm magnetic magnetic data data are are represented represented (Figure(Figure S8).S8).
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FigureFigure 11. 11.Residual Residual of theof the Y componentY component of Swarmof Swarm Bravo Bravo magnetic magnetic field field after after the the occurrence occurrence of of the the Mw Figure 11. Residual of the Y component of Swarm Bravo magnetic field after the occurrence of the 6.4 2019-04-05Mw 6.4 2019-04-05 earthquake. earthquake. The satellite The passedsatellite abovepassed the above epicenter the epicenter some minutes some beforeminutes the before earthquake the Mw 6.4 2019-04-05 earthquake. The satellite passed above the epicenter some minutes before the earthquake occurrence; thus, no vertical black line is represented here (see previous figures where occurrence;earthquake thus, occurrence; no vertical thus, black no ve linertical is representedblack line is represented here (see previous here (see figures previous where figures this where line was this line was plotted for more details). The vertical green line is the candidate point where the plottedthis line for morewas plotted details). for The more vertical details). green The line vert is theical candidategreen line pointis the where candidate the earthquake-induced point where the earthquake-induced phenomena are supposed to start. We selected this point, which is the start of a phenomenaearthquake-induced are supposed phenomena to start. We are selected supposed this topoint, start. We which selected is the this start point, of a long which “train” is the of start anomalies of a long “train” of anomalies in the track that persist for more than 9 min; other anomalies start after in thelong track “train” that of persist anomalies for more in the than track 9 min;that otherpersis anomaliest for more than start 9 after min; about other 15 anomalies min, and start thus after cannot about 15 min, and thus cannot be generated by acoustic gravity waves. In the Supplementary be generatedabout 15 min, by acousticand thus gravity cannot waves. be generated In theSupplementary by acoustic gravity Materials, waves. more In the details Supplementary and the other Materials, more details and the other available Swarm magnetic data are represented (Figure S9). availableMaterials, Swarm more magnetic details and data the are other represented available Sw (Figurearm magnetic S9). data are represented (Figure S9).
Figure 12. Residual of the Y component of Swarm Alpha magnetic field after the occurrence of the FigureFigure 12. 12.Residual Residual of of the the Y Y component component ofof SwarmSwarm Alpha magnetic magnetic field field after after the the occurrence occurrence of the of the Mw 5.6 2019-04-07 earthquake. The vertical black line in the lower plot represents the point where the MwMw 5.6 5.6 2019-04-07 2019-04-07 earthquake. earthquake. The vertical vertical black black line line in the inthe lower lower plot plotrepresents represents the point the where point wherethe satellite crosses the earthquake latitude. The vertical green line is the candidate point where the satellite crosses the earthquake latitude. The vertical green line is the candidate point where the theearthquake-induced satellite crosses the phenomena earthquake are latitude. supposed The to verticalstart. We green selected line this is thepoint candidate because it point is the where start of the earthquake-induced phenomena are supposed to start. We selected this point because it is the start of earthquake-inducedthe only anomaly presented phenomena in the are shown supposed track. to During start. We theselected time of the this occurrence point because of the it earthquake, is the start of the only anomaly presented in the shown track. During the time of the occurrence of the earthquake, thethe only satellite anomaly was presented below -70° in geographical the shown track. latitude, During and thus, the time the data of the are occurrence cut. In the ofSupplementary the earthquake, the satellite was below -70° geographical latitude, and thus, the data are cut. In the Supplementary theMaterials, satellite was more below details -70 and◦ geographical the other available latitude, Swarm and magnetic thus, the data data are are represented cut. In the (Figure Supplementary S10). Materials,Materials, more more details details and and the the other other available available SwarmSwarm magnetic data data are are represented represented (Figure (Figure S10). S10).
Remote Sens. 2020, 12, 1166 12 of 21
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FigureFigure 13. 13.Residual Residual of of the the Y Y component component ofof SwarmSwarm Charlie magnetic magnetic field field after after the the occurrence occurrence of ofthe the MwMw 5.6 5.6 2019-04-07 2019-04-07 earthquake. earthquake. The The vertical vertical black black line line in the in the lower lower plot plot represents represents the point the pointwhere where the thesatellite satellite crosses crosses the the earthquake earthquake latitude. latitude. The The vert verticalical green green line line is isthe the candidate candidate point point where where the the earthquake-inducedearthquake-induced phenomena phenomena are are supposed supposed toto start.start. As As in in the the previous previous track, track, this this point point is isthe the start start ofof the the only only anomaly anomaly presented presented in in the the track.track. The data of Charlie Charlie are are ve veryry similar similar to to the the ones ones of ofAlpha Alpha forfor this this case case study. study. During During the the time time of of the the occurrence occurrence ofof thethe earthquake, the the satellite satellite was was below below -70°70 − ◦ geographicalgeographical latitude, latitude, and and thus, thus, the the data data are are cut. cut. In In the the Supplementary Supplementary Materials, Materials, more more details details and and the otherthe availableother available Swarm Swarm magnetic magnetic data data are representedare represented (Figure (Figure S10). S10).
4. DiscussionThe acoustic and gravity Interpretation waves induced by seismic activities are only a type of a great variety of phenomenaThe 12 that selected could tracks affect associated the ionosphere. to 10 seismic For this events reason, have several been analyzed disturbances to search affect for these a possible figures. Therefore,linear regression to measure between the time the oftime the interval arrival ofof thethe possiblearrival of disturbance a supposed inducedco-seismic by gravity the seismic wave event, in a particularthe ionosphere change and in the the distance waveform, between concentrating the epicentre in theand part the ofSwarm the track satellite, that as started represented after some in minutesFigure of14. the The seismic intercept event, has been was selected.fixed to the We origin excluded of the the axis first as the minute time ofto eachcover track,a null becausedistance an acousticneeds to gravity be zero. wave The requires obtained about slope 3.5is (0.00163 min to reach± 0.00014) Swarm min/km altitude that (~450kmcorresponds or more). to a propagation The latitude of thevelocity satellite of (10.04 was also ± 0.85) taken km/s. into The account R2 = to0.92 understand denotes a ifgood the disturbanceagreement with could this be linear due to regression, the standard geomagneticconfirming that activity the two ofthe quantities Earth’s plotted polar regions.in the graph We seem admit to be that linearly this interpretation correlated. Although is not totallythis objectivecorrelation and unique,is pretty althoughgood, the su prffiopagationciently reasonable. speed for this For aphenomenon quick comparison seems andto be validation, higher than we we also presentmight inexpect the Appendix for this kindA an of automaticwaves. We approachpropose that that actually is totally this objective could be andcaused practically by two different confirms ourinvolved results. phenomena: one from the Earth’s surface that reaches the maximum electron density altitudeFor the (hmF2 earthquake or altitude that occurred of ionospheric on 2014-02-18, layer F2), only and the tracksanother of physical Bravo and phenomenon Charlie (Figures that 3 propagates from this altitude to the satellite position. and4) are provided as Swarm Alpha was not in nominal conditions during the passage over the epicentral area. Most of the data present a discrepancy between ASM and VFM measurements (Flag_F = 16), and the attitude information was interpolated with the nearest points for lack of data from two or all three star-cameras. These conditions were probably due to the early stage of the mission that we analyzed. An earthquake happened offshore Chile on 2015-11-11 at a depth of 10 km between the Nazca and South-American plates. In this case, a perturbation was visible just north of the epicentre and we cannot exclude that this could be an electromagnetic phenomenon coming directly from the fault. There was a certain symmetry of the signal with respect to the epicentre latitude. The ionospheric disturbance was possibly associated with the high magnitude earthquake (Mw 6.9) considered in this case (Figure6).
4. Discussion and Interpretation The 12 selected tracks associated to 10 seismic events have been analyzed to search for a possible linear regression between the time interval of the arrival of a supposed co-seismic gravity wave in
Remote Sens. 2020, 12, 1166 13 of 21 the ionosphere and the distance between the epicentre and the Swarm satellite, as represented in Figure 14. The intercept has been fixed to the origin of the axis as the time to cover a null distance needs to be zero. The obtained slope is (0.00163 0.00014) min/km that corresponds to a propagation ± velocity of (10.04 0.85) km/s. The R2 = 0.92 denotes a good agreement with this linear regression, ± confirming that the two quantities plotted in the graph seem to be linearly correlated. Although this correlation is pretty good, the propagation speed for this phenomenon seems to be higher than we might expect for this kind of waves. We propose that actually this could be caused by two different involved phenomena: one from the Earth’s surface that reaches the maximum electron density altitude (hmF2 or altitude of ionospheric layer F2), and another physical phenomenon that propagates from thisRemote altitude Sens. 2020 to the, 12, satellitex FOR PEER position. REVIEW 13 of 20
9
data 8 Linear fit
7
6
time (min) 5
Equation y = a + b*x Plot time 4 Intercept 0 (fixed) Slope 0.00163 ± 1.30033E-4 Residual Sum of Square 27.87253 Pearson's r 0.96661 R-Square (COD) 0.93433 3 Adj. R-Square 0.92836
1000 2000 3000 4000 5000 6000 distance (km)
FigureFigure 14. 14.Relation Relation betweenbetween thethe timetime interval of the the a arrivalrrival of of the the co-seismic co-seismic gravity gravity wave wave in inthe the ionosphere in function of the distance between the epicentre and the Swarm satellite. ionosphere in function of the distance between the epicentre and the Swarm satellite.
AA sketch sketch of of the the proposed proposed propagation propagation mechanismmechanism is is shown shown in in Figure Figure 15. 15 A. Asimple simple model model was was implemented with a vertical propagation with velocity v1 until hmF2 and a second velocity v2 from implemented with a vertical propagation with velocity v1 until hmF2 and a second velocity v2 from the projection of the epicentre at hmF2 until the satellite position. The altitude of the F2 layer was the projection of the epicentre at hmF2 until the satellite position. The altitude of the F2 layer was determined by the IRI-2016 model and listed in Table 1. We supposed that the velocity v1 and v2 were determined by the IRI-2016 model and listed in Table1. We supposed that the velocity v 1 and v2 equal for all the events, and thus, we determined which combination of v1 and v2 can reduce the were equal for all the events, and thus, we determined which combination of v1 and v2 can reduce difference with the measured times. “v1” and “v2” were selected in the range between 0.10 km/s and the difference with the measured times. “v ” and “v ” were selected in the range between 0.10 km/s 50.00 km/s with a step of 0.01 km/s. We also1 take into2 account that the different air temperature T andaffects 50.00 the km mechanical/s with a step velocity of 0.01 of kmpropagation/s. We also by take a factor into of account √𝑇 [32]. that Thus, the the diff surfaceerent air (2 temperaturem height) √ T atemperatureffects the mechanical has been retrieved velocity from of propagation the climatological by a factor archive of ECMWFT [32]. ERA-Interim Thus, the surfacefor the (210 m height) temperature has been retrieved from the climatological archive ECMWF ERA-Interim for earthquakes, and the velocity v1 was multiplied by 𝑇/298𝐾 . The division by 298K assures to obtain √ thethe 10 result earthquakes, referred andto the the standard velocity temperature v1 was multiplied of 25°C. byThe bestT/298 combinationK . The division that fits by our 298K data assures (i.e., tothe obtain one with the result the minimum referred residuals) to the standard was v1 = temperature2.20 km/s (at temperature of 25 ◦C. The of 25°C) best combinationand v2 = 16.07 thatkm/s. fits ourFrom data the (i.e., dispersion the one withof the the measurements minimum residuals) versus the was model, v1 = we2.20 estimated km/s (at an temperature uncertainty ofon 25the◦ C) andvelocitiesv2 = 16.07 of about km/s. Δ Fromv1 = 0.3 the km/s dispersion and Δv2 = of 3 thekm/s. measurements We note that the versus velocity the v model,1 is in agreement we estimated with an uncertaintythe known on velocities the velocities in the ofliterature about ∆ forv1 acoustic= 0.3 km gravity/s and ∆wavesv2 = 3(e.g., km/ [9]).s. We note that the velocity v1 is in agreementA comparison with the between known velocitiesthe calculated in the and literature the measured for acoustic times gravity needed waves to propagate (e.g., [9]). from epicentre to the satellite is represented in Figure 16. The red line represents the ideal case, i.e., when the model was identical to the measurements. The sum of the residual between the time estimated from the model and the measured one from satellite data was reported. The calculated values for the model with two velocities used the best-obtained velocity estimations. We note that in the second model (b), two cases were correctly described by the model as they are on the ideal trend, while the others were under- or overestimated. As also underlined by the lower value of the sum of the residuals, the model with two velocities estimates better the time of propagation of the disturbance from the epicenter to the satellite, with a lower dispersion of data in the plot and closer to the ideal case (red line). This statistical evidence deposes in favour of our assumption of a gravity wave that mechanically propagates until F2 layer making oscillating the high number of free electrons in this region and starting a scattering that propagates at least to the Swarm satellite altitudes (about 440– 500 km above sea level). Considering also some literature [33,34], we tested the possibility that the second propagation follows the magnetic field lines strictly. We found that the results were worse than the simple straight propagation, thus, even if the perturbation could affect the magnetic field, the disturbance probably did not strictly follow the magnetic field lines.
RemoteRemote Sens.Sens. 20202020,, 1212,, 1166x FOR PEER REVIEW 1414 of 21 20
v2
v1
Figure 15. Possible mechanism of propagation of the disturbance from the epicentre to the Swarm Figure 15. Possible mechanism of propagation of the disturbance from the epicentre to the Swarm satellite. From the lithosphere to the F2 ionospheric layer, an acoustic gravity wave is probably the satellite. From the lithosphere to the F2 ionospheric layer, an acoustic gravity wave is probably the mechanism, and from F2 to the Swarm position, some electromagnetic scattering could be involved mechanism, and from F2 to the Swarm position, some electromagnetic scattering could be involved (see the text for further discussion). (see the text for further discussion). A comparison between the calculated and the measured times needed to propagate from epicentre to the satellite is represented in Figure 16. The red line represents the ideal case, i.e., when the model was identical to the measurements. The sum of the residual between the time estimated from the model and the measured one from satellite data was reported. The calculated values for the model with two velocities used the best-obtained velocity estimations. We note that in the second model (b), two cases were correctly described by the model as they are on the ideal trend, while the others were under- or overestimated. As also underlined by the lower value of the sum of the residuals, the model with two velocities estimates better the time of propagation of the disturbance from the epicenter to the satellite, with a lower dispersion of data in the plot and closer to the ideal case (red line). This statistical evidence deposes in favour of our assumption of a gravity wave that mechanically propagates until F2 layer making oscillating the high number of free electrons in this region and starting a scattering that propagates at least to the Swarm satellite altitudes (about 440–500 km above sea level). Considering also some literature [33,34], we tested the possibility that the second propagation follows the magnetic field lines strictly. We found that the results were worse than the simple straight propagation, thus, even if the perturbation could affect the magnetic field, the disturbance probably did not strictly follow the magnetic field lines.
Figure 16. Comparison of the calculated time versus the measured one to propagate from epicenter to the satellite. The red line represents the ideal case, i.e., when the model is identical to the measurements. a) A model with one velocity. b) A model with two velocities. Each graph reports the corresponding sum of the residuals of the model with respect to the measured data. The two-velocity model shows the lowest residual.
Remote Sens. 2020, 12, x FOR PEER REVIEW 14 of 20
v2
v1
Figure 15. Possible mechanism of propagation of the disturbance from the epicentre to the Swarm satellite. From the lithosphere to the F2 ionospheric layer, an acoustic gravity wave is probably the Remote Sens.mechanism,2020, 12, 1166and from F2 to the Swarm position, some electromagnetic scattering could be involved 15 of 21 (see the text for further discussion).
FigureFigure 16. 16.Comparison Comparison of of the the calculated calculated timetime versusversus thethe measuredmeasured oneone toto propagatepropagate from epicenter to theto satellite. the satellite. The red The line red represents line represents the ideal the case, ideal i.e., case, when i.e., the when model the is identical model is to identical the measurements. to the (a)measurements. A model with a) one A velocity.model with (b) one A model velocity. with b) twoA model velocities. with two Each velocities. graph reports Each graph the corresponding reports the sumcorresponding of the residuals sum ofof the residuals model with of the respect model to with the measuredrespect to the data. measured The two-velocity data. The two-velocity model shows themodel lowest shows residual. the lowest residual.
ToTo finally finally compare compare the the two two approachesapproaches describing the the data data (one-velocity (one-velocity or ortwo-velocity two-velocity model), model), wewe used used the the Akaike Akaike Information Information CriterionCriterion (AIC) developed by by Akaike, Akaike, 1973 1973 [35]. [35 ].In Incase case of offew few parametersparameters a a “corrected” “corrected” index index AICcAICc cancan be used. This This criterion criterion was was used used to to choose choose the the best best model model (the one that presents the minimum AIC, or AICc, later described) and select which variables were really fundamental to the system. The AIC is defined as:
AIC = 2K 2 log(L) (1) − where K is the number of estimated parameters, i.e., the degree of freedom and L is the maximum of the likelihood function. For this paper, we used the following equation to estimate the log(L) :
1 1 RSS2 log(L) = nσ2 = n (2) −2 −2 n where n is the number of samples and RSS is the Residual Sum of Squares. If the dataset on which the model is evaluated contains a small number of elements, as in our case, a correction factor must be introduced, estimating a second coefficient, called AICc:
2K(K + 1) AICc = AIC + (3) n K 1 − − To calculate the values of AIC and AICc for our two models, we followed the approach of Snipes and Taylor, 2014 [36], even if they applied this criterion to a vastly different case study. Table2 reports the parameters and the AIC and AICc coefficients obtained for the two models. The number of parameters has been increased by one to consider an error coefficient in the model. Despite the height of the F2 layer (hmF2) and the temperature are two parameters used in the second model, they do not add any degree of freedom to the same model, since they are fixed. Remote Sens. 2020, 12, 1166 16 of 21
Table 2. Results of the Akaike Information Criterion applied to the two used models.
Number of Number of Residual Sum of AIC AICc Parameters K Samples Square RSS [s2] Model 1 (one velocity) 2 12 1.09 105 99.0 100.3 × Model 2 (two velocities) 3 12 6.07 104 94.9 97.9 ×
The AICc (and even AIC) suggests that the model with two velocities better describes the magnetic disturbance identified in the 12-track dataset. From a physical point of view, this is promising, since the model with one velocity gives a speed that is not compatible with known phenomena of the interaction of lithosphere, atmosphere and ionosphere; otherwise, the first velocity of the second model is compatible with an acoustic gravity wave.
5. Conclusions After a systematic analysis of the first 5.3 years of Swarm magnetic data around the Mw5.5+ earthquakes, we found that 12 Swarm satellite tracks recorded disturbances following earthquakes of magnitude Mw5.6 to 6.9. We underline that we limited our search for possible co-seismic effects to a subset of earthquakes selected in function of their depth and magnitude. Even if this subset could exclude some possibility to record some additional effect, we were driven by the necessity to exclude the deeper and lower magnitude events that are unfeasible to produce any seismic effect in the ionosphere. In addition, we do not expect particular difference with other selection criteria. However, more energetic seismic events were recorded during this period (included three Mw8+ earthquakes: two in Chile and one in Mexico), but we did not find possible co-seismic ionospheric disturbances produced by these large events. This is due to the fact that the Swarm satellites did not fly just over the epicentral area at the time of the earthquake occurrence. This explains why we found geomagnetic ionospheric disturbances only for almost medium magnitude earthquakes. The linear regression of the time versus the distance between the earthquake occurrence and the record of the disturbance by Swarm satellites seems to confirm that the seismic events possibly induce the disturbances. To explain these disturbances, a model that combines two different propagation ways has been proposed with promising result. The model considers an acoustic gravity wave as the way to propagate the earthquake disturbance up to the F2 ionospheric layer, i.e., the layer with the maximum ionisation. The impact of the acoustic gravity waves on this layer could induce some electromagnetic scattering that propagates in the upper ionospheric layer, reaching the Swarm satellites. The propagation velocities, according to our data, are (2.2 0.3) km/s with a 25 C of surface air temperature for the acoustic ± ◦ gravity waves and (16 3) km/s for the electromagnetic scattering propagation. We note that the ± approximation to the same velocity for all the seismic events is a limitation and, in particular, it does not take into account, e.g., the different local time: future improvements could introduce the importance of the local time together with some other parameters that would take into account the different chemical and physical conditions of the atmosphere and ionosphere where the phenomena propagate. This double-velocity model has better statistical reliability, providing a lower AIC than the one with only one velocity. In order to validate the mostly subjective criteria chosen in this work to select the co-seismic anomalies, we developed an automatic algorithm that detects the co-seismic perturbations based on objective criteria (see AppendixA). The principal results of this paper were also confirmed by this automatic approach to detect the anomalies. Nevertheless, the automatic system was not yet able to achieve the quality with which a researcher can evaluate the signal of the satellite track to discriminate and choose the effects and causes of the detected disturbances. A future improvement of the automatic procedure can include the analysis of the signal frequency for not only searching a disturbance along the satellite track but also some particular frequencies without usually presenting in other parts of the track. Remote Sens. 2020, 12, 1166 17 of 21
A larger constellation of Low Earth Orbit satellites equipped with magnetometers could improve the coverage, i.e., the capability to record and deeper understand this type of signal. The recent launch of the Chinese Seismo-electromagnetic satellite in 2018 could contribute to this endeavour greatly.
Supplementary Materials: The following are available online at http://www.mdpi.com/2072-4292/12/7/1166/s1. Figures S1–S11: The output tracks where some possible co-seismic effects on magnetic field have been detected and one example where we do not found any evidence of possible earthquake-source disturbance. Author Contributions: Conceptualization, D.M., and A.D.S.; methodology, D.M. and A.D.S.; software, D.M. and S.A.C.; validation, S.A.C., G.C. and A.P.; formal analysis, D.M.; investigation, D.M. and A.D.S.; resources, D.M., A.D.S., S.A.C.; data curation, D.M. and S.A.C.; writing—original draft preparation, D.M. and A.D.S.; writing—review and editing, all authors; visualization, D.M. and A.D.S.; supervision, A.D.S.; project administration, A.D.S. and S.J.; funding acquisition, A.D.S. and S.J. All authors have read and agreed to the published version of the manuscript. Funding: This research was funded by European Space Agency (SAFE project), Agenzia Spaziale Italiana (Limadou-science project), International Space Science Institute in Bern and Beijing (ISSI-BJ, “The electromagnetic data validation and scientific application research based on CSES satellite” project); the APC was funded by “Startup Foundation for Introducing Talent of NUIST” (Grant No. 2243141801036). Acknowledgments: We thank the European and Italian Space Agencies for funding these kinds of studies (see Funding). Part of this work has been performed for the project ISSI-BJ “The electromagnetic data validation and scientific application research based on CSES satellite”. We thank the anonymous referees and the editor, who, with their useful suggestions, have helped to improve our manuscript significantly. Conflicts of Interest: The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.
Appendix A. Automatic Detection of Possible Co-Seismic Anomalies In this Appendix, a completely automatic procedure to detect possible co-seismic anomalies is presented. The advantage of this procedure, with respect to the one presented in the paper, is that it is completely objective and re-producible by the defined criteria. With this procedure, we want to support the results of our work. However, we recognize that an automatic procedure cannot fully evaluate the signal the way a human can, even if some constraints can replace our considerations to the selected anomalies presented in our paper. The automatic procedure starts from the filtered signal, i.e., the magnetic Y component of the Swarm satellite minus the IGRF-12 model and filtered with high pass filter with a 0.25 Hz frequency cut-off. The geomagnetic latitude is computed, taking into account the dipole calculated with the IGRF-12 model. Only the data inside 50 and +50 are taken into account to avoid the auroral − ◦ ◦ and polar regions that are geomagnetically too active to identify any possible co-seismic signal. The Root Mean Square of the whole track is computed in analogy with the procedure used in [22,27,37]. A moving window of 20 s length is then used from 1 min after the earthquake occurrence until to search the first anomaly in time if any. One minute was chosen as the minimum time that the signal needs at least to be transmitted from the epicentre to the satellite altitude ( 450km). A pure electromagnetic ≥ wave requires less than one second, but this eventual phenomenon was not the goal of this paper, and a pure gravity wave would take around 3.5 min. The anomaly is defined with a threshold (kt) equal to 2.0 comparing its root mean square rms into the moving window with the one of the whole track, i.e., rms/RMS > kt. This threshold corresponds to about two standard deviations commonly used in similar approaches. Thresholds of 1.5, 1.75, 2.25 and 2.5 have been tested too, but they provide worst results (i.e., lower correlation coefficient of the results) with respect to kt = 2.0. The automatic procedure found anomalies in 31 tracks out of 37 investigated tracks, i.e., 83.8%. This number is much higher than the selected anomalies in the main text (12). Despite this, we need to note that several anomalies are not reliable; for example, they occur too early in relation to the distance from the earthquake epicenter or too late and close with respect to the earthquake epicenter. The latter case could be a continuation of the co-seismic effect in ionosphere after its arrival. Remote Sens. 2020, 12, x FOR PEER REVIEW 17 of 20
evaluate the signal the way a human can, even if some constraints can replace our considerations to the selected anomalies presented in our paper. The automatic procedure starts from the filtered signal, i.e., the magnetic Y component of the Swarm satellite minus the IGRF-12 model and filtered with high pass filter with a 0.25 Hz frequency cut-off. The geomagnetic latitude is computed, taking into account the dipole calculated with the IGRF-12 model. Only the data inside -50° and +50° are taken into account to avoid the auroral and polar regions that are geomagnetically too active to identify any possible co-seismic signal. The Root Mean Square of the whole track is computed in analogy with the procedure used in [22,27,37]. A moving window of 20 s length is then used from 1 min after the earthquake occurrence until to search the first anomaly in time if any. One minute was chosen as the minimum time that the signal needs at least to be transmitted from the epicentre to the satellite altitude (≥450km). A pure electromagnetic wave requires less than one second, but this eventual phenomenon was not the goal of this paper, and a pure gravity wave would take around 3.5 min. The anomaly is defined with a threshold (kt) equal to 2.0 comparing its root mean square rms into the moving window with the one of the whole track, i.e., rms/RMS > kt. This threshold corresponds to about two standard deviations commonly used in similar approaches. Thresholds of 1.5, 1.75, 2.25 and 2.5 have been tested too, but they provide worst results (i.e., lower correlation coefficient of the results) with respect to kt = 2.0. The automatic procedure found anomalies in 31 tracks out of 37 investigated tracks, i.e., 83.8%. This number is much higher than the selected anomalies in the main text (12). Despite this, we need Remoteto note Sens. that2020 , several12, 1166 anomalies are not reliable; for example, they occur too early in relation to 18the of 21 distance from the earthquake epicenter or too late and close with respect to the earthquake epicenter. The latter case could be a continuation of the co-seismic effect in ionosphere after its arrival. The distance from the epicentre and satellite versus the time for the 31 tracks is represented in The distance from the epicentre and satellite versus the time for the 31 tracks is represented in Figure A1. The time to reach the epicentre from the hypocenter has been estimated by a velocity Figure 17. The time to reach the epicentre from the hypocenter has been estimated by a velocity of 4 of 4 km/s and subtracted from the data. The linear regression provides a slope of (2.60 0.41) 10 3 km/s and subtracted from the data. The linear regression provides a slope of (2.60 ± 0.41) 10±−3 min/km − min/km that corresponds to a mean propagation velocity of (6.4 1.0) km/s. The obtained velocity is that corresponds to a mean propagation velocity of (6.4 ± 1.0) km/s.± The obtained velocity is quite quitesimilar similar to the to theone one calculated calculated in the in themain main text, text, but but thethe dispersion dispersion of the ofthe data data is higher is higher (in (infact, fact, the the correlationcorrelation coe coefficientfficient is is much much lower). lower).
FigureFigure A1. 17.Time Time after after the the earthquakeearthquake occurrence versus versus the the distance distance between between the the epicentre epicentre and and the the satellitesatellite for for the the 31 31 anomalies anomalies automatically automatically detected. detected The. The time time of propagationof propagation of theof the seismic seismic wave wave from thefrom hypocenter the hypocenter to the epicentre to the epicentre has been has subtracted. been subtracted.
InIn analogy analogy with with the the analyses analyses of ofthe the mainmain text, th thee model model with with two two velocities velocities has has been been tested tested with with thethe same same approach, approach, using using all all the the 31 31 anomaliesanomalies and taking into into account account the the air air temperature temperature and and the the heightheight of hmF2of hmF2 in additionin addition to the to simplethe simple model mode withl onewith velocity. one velocity. Figure Figure A2 shows 18 shows the results the results obtained byobtained the models by withthe models one and with two one velocities and two for thevelociti automaticallyes for the detectedautomatically anomalies. detected Additionally, anomalies. in thisAdditionally, case, the model in this with case, two the velocities model with presents two veloci lowerties residuals presents with lower respect residuals to the with first respect one. to We the note thatfirst the one. residuals We note are that about the 10residuals times more are about than the10 times corresponding more than calculus the corresponding in the main calculus text (Figure in the 16 ). This is partly due to the higher number of cases (31 instead of 12), the longer analyzed time (until about 30 m instead of 20 m) and, finally, to the lower quality of the co-seismic anomaly detection of the automatic approach. The best obtained velocities are v1 = 0.7 km/s (at temperature of 25 ◦C) and v2 = 14.8 km/s. The first velocity is very low with respect to the one obtained with the supervised track selection (2.2 km/s) and also too low for a gravity wave. The second velocity is closer to the result in the main text (16.1 km/s). Furthermore, this automatic approach confirms that v2 is greater than v1 and, finally, confirms the order of magnitude of the results. Remote Sens. 2020, 12, x FOR PEER REVIEW 18 of 20
main text (Figure 16). This is partly due to the higher number of cases (31 instead of 12), the longer analyzed time (until about 30 m instead of 20 m) and, finally, to the lower quality of the co-seismic anomaly detection of the automatic approach. The best obtained velocities are v1 = 0.7 km/s (at temperature of 25 °C) and v2 = 14.8 km/s. The first velocity is very low with respect to the one obtained with the supervised track selection (2.2 km/s) and also too low for a gravity wave. The second velocity Remoteis closer Sens. to2020 the, 12 result, 1166 in the main text (16.1 km/s). Furthermore, this automatic approach confirms19 of that 21 v2 is greater than v1 and, finally, confirms the order of magnitude of the results.
FigureFigure A2. 18. Comparison of the times obtainedobtained fromfrom thethe modelsmodels andand thosethose measuredmeasured withwith oneone andand two two velocitiesvelocities for for the the automatically automatically detected detected anomalies. anomalies. The The red red line line represents represents the the ideal ideal case, case, i.e., wheni.e., when the modelthe model equals equals the measurements. the measurements.
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