Method and system for monitoring particle deposition in the magnetosphere

Abstract

A method (100) for monitoring particle deposition in the magnetosphere comprises the steps of: detecting (101) charged magnetospheric particles by means of at least one particle detector (10) installed on at least one satellite vehicle (1) in orbit (3), associating the detected particles with respective detection data; processing (102) the detection data to associate respective kinetic energy estimates or kinetic energy measurements with the detected magnetospheric particles; obtaining a first count value N H (104) relating to the number of charged particles detected over a time period, the first count value being associated with relatively higher kinetic energy estimates or kinetic energy measurements comprised in a first energy range; obtaining a second count value N L (105) relating to the number of charged particles detected over said time period, the second count value N L being associated with relatively lower kinetic energy estimates or kinetic energy measurements comprised in a second energy range; detecting (106) a relative variation value of the second count value N L with respect to the first count value N H ; determining (107) that a pulse event of particle deposition in the magnetosphere - MPP event - has occurred over the aforementioned time period, comparing the aforementioned variation value with a threshold value; assigning (109) to said MPP event the geomagnetic longitude and time at which said MPP event occurred; defining (110) one or more groups of MPP events, each group comprising MPP events occurring over a time range, at the same geomagnetic longitude or at relatively close geomagnetic longitudes; identifying (111) a group of MPP events as indicative of a surface-originated activity, such as a pre-seismic activity or a seismic activity, based on the number of MPP events comprised in the group and / or based on the associated variation value found in the detection step (106).

Description

TECHNICAL FIELD

[0001] The present invention relates to the technical field of satellite systems for monitoring particles in space, in particular to the technical field of satellite systems for acquiring and processing data related to the activity of particles. In particular, the present invention relates to a method and a system for monitoring particle deposition in the magnetosphere, which can be implemented using particle probes. For example, such a method and such a monitoring system can be used for identifying possible active areas for pre-seismic activity and providing alerts for potential activity related to earthquakes. The monitoring system and method can be used in general for monitoring electromagnetic disturbances of the Earth's magnetosphere caused by tectonic phenomena. BACKGROUND

[0002] PRIOR ART

[0003] Demonstrating with high and reliable statistical significance a method for associating physical signals detectable by current technology with earthquakes is a difficult problem to solve. Previous attempts over the past few decades involved several research groups in several countries affected by intense seismic activity, including groups in Italy, Greece, the United States, Japan and China. The methods used involved ground measurements and, more recently, measurements made using space instruments.

[0004] Several cases of anomalous emission of electromagnetic signals with peculiar properties have been reported, which coincided in time and space with high-energy earthquakes, i.e. particularly high-intensity earthquakes. These results, although interesting, are limited to establishing casual evidence of earthquakes and ground or space measurements. There are many reasons for this: lack of systematic studies of this type of influence over a sufficiently long period of time (years), reproducibility of results, high background noise affecting the measurement process, weak overall statistical evidence. None of the related attempts made so far has been supported by a statistically very significant post-test determination of the probability of occurrence of these results.

[0005] Since the late 1980s, research has been conducted on the possible correlation between special magnetospheric particle events and earthquakes. The first work on this subject was produced by A.M. Galper, et al. in 1989, for example, as described in:

[0006] - S. Yu. Aleksandrin, A.M. Galper, L.A. Gritsanenko, S.V. Kordonsky, L.V.

[0007] Aleksandrin, S.Yu.; Galper, A.M.; Gritsanenko, L.A.; Kordonsky, S.V.; Kuznetsov, V.N.; Murashev, A.M.; Pikoz, P.; Sgrigna, V.; Volnov, S.A., 2003, "High-energy charged particle bursts in near-Earth space as a precursor of earthquakes", Annals of Geophysics, Vol. 21, pp. 597-602.

[0008] Galper, A. M.; Grishantzeva, L. A.; Koldashov, S. V.; Maslennikov, L. V.;

[0009] Murashov, A. M.; Picozza, P.; Sgrigna, V.; Voronov, S. A., "High-energy charged particle bursts in the near-Earth space as earthquake precursors", Annales Geophysicae, 21, 597-602 (2003)); and

[0010] Galper, A. M., et al., "Connection of the fluxes of charged particles of high energy in radiation belt with the Earth seismicity", Cosmic Research, 27, 789-792 (1989)).

[0011] (1989)).

[0012] In these studies, an attempt was made to study a method for obtaining a correlation between seismic events and electromagnetic disturbances. The method of Galper et al. is based on:

[0013] - a magnetosphere and lithosphere coupling model based on the propagation of electromagnetic waves propagating along the magnetic L-shell (defined as the field line identified in terms of distance in surface rays, here the magnetic field line intersects the equatorial plane of the Earth's magnetosphere) and on the interaction of these waves with the particles trapped in the L-shell (phenomenon of particle precipitation);

[0014] - the selection of earthquakes with magnitude (in the MMS (Moment Magnitude) scale) M≥5 (this is a rather low value and therefore leads to a correlation of low statistical significance between magnetospheric particle precipitation and earthquakes);

[0015] - the identification of particle precipitations based on the increase or burst of high-energy particles produced by wave-particle resonances. These particle precipitations are observed by satellites with suitable devices for detecting magnetospheric particles;

[0016] - the time correlation between the deposition of magnetospheric particles and seismic events, based on the time difference between the deposition of magnetospheric particles and the occurrence of seismic events in the same L-shell, within a narrow range.

[0017] However, the results of the above studies are minimal from a statistical point of view, due to the chosen method and to the chosen population of earthquakes, whose magnitude is too low. In recent years, since these first attempts, no substantial improvements have been made.

[0018] For example, Pulinets & Boyarchuk in Pulinets, S. & Boyarchuk, K., “Ionospheric Precursors of Earthquakes”, Springer (2004) gives a general description of the above method. In this publication, the chapter dedicated to the detection of the magnetospheric particle deposition is based on the aforementioned article by Galper et al.

[0019] In Hayakawa M., “Earthquake Prediction with Radio Techniques”, (Singapore, John Wiley & Sons, 2015) a reliable description of the electromagnetic waves possibly associated with earthquakes can be found. In this publication and in other publications:

[0020] - Hayakawa, M., Yoshino, T. & Morgounov, V. A., “On the possible influence of seismic activity on the propagation of magnetospheric whistlers at low latitudes”, Phys. Earth and Planet. Interiors, 77, 97-108 (1993);

[0021] M. Hayakawa, Y. Hobara, K. Ohta, & K. Hattori, "The ultra-low frequency magnetic disturbances associated with earthquakes", Earthquake Sci., 24(6), 523-534 (2011);

[0022] K. Ohta, J. Izutsu, A. Schekotov, & M. Hayakawa, "The ULF / ELF electromagnetic radiation before the 11 March 2011 Japanese earthquake", Radio Science, 48, 589-596 (2013);

[0023] Indirect evidence is provided regarding the observed emission of low-frequency electromagnetic waves associated with large magnitude earthquakes. These ground-based observations focus on the detection of ULF and VLF waves using instruments located on the ground, the emission of which can occur simultaneously with strong earthquakes. See also the publication:

[0024] J. L. Currie & J. L. Waters, "On the use of geomagnetic indices and ULF waves for earthquakes precursor signatures", J. Geophys. Res. Space Physics, 119, 992-1003 (2014);

[0025] Res. Space Physics, 119, 992-1003 (2014);

[0026] Park, S. A., Johnston, M. J. S., Madden, T. R., Morgan, F. D. & Morrison, H. F., “Electromagnetic precursors to earthquakes in the ULF band: a review of observations and mechanisms”, Rev. Geophys., 31, 117-132 (1993).

[0027] In addition, in view of the spatial and temporal proximity of the magnetospheric anomalies to certain earthquakes, some cases of magnetospheric anomalies, referred to as total electron content (TEC), are also discussed, for example, in the publication: M. Ekawa, Earthquake Prediction Using Radio Techniques (John Wiley & Sons, Singapore).

[0028] However, none of the aforementioned studies carried out a systematic study nor discussed a global statistical analysis of the possible correlation between ULF / VLF signals and / or TEC anomalies and earthquakes, even if it is possible to identify candidates therefrom.

[0029] The DEMETER satellite constellation (operating between 2004 and 2010) published observations of wave perturbations in the ionosphere, spatially and temporally adjacent to large magnitude earthquakes. See, for example, the publications:

[0030] Onishi, T., Parrot, M. & Berthelier, J.-J., “The DEMETER mission, recent investigations on ionospheric effects associated with man-made activities and seismic phenomena”, Comptes Rendus Physique, 12, 160-170 (2011); and

[0031] M. Parrot, J. -J. Berthelier, J. -P. Lebreton, J. -A. Sauvaud, O. Santolik and J. Blecki, "Examples of unusual ionospheric observations made by the DEMETER satellite over seismic regions", Physics and Chemistry of the Earth, 31, 486-495 (2006).

[0032] These observations from space (from an altitude of about 700 km) show significant detections for VLF and LF waves. However, a global analysis of the DEMETER data in temporal proximity to the earthquakes does not support a highly statistically significant correlation between these wave emissions and the earthquakes.

[0033] In practice, to date, no satisfactory demonstration (based on rigorous and comprehensive statistical analysis) of a systematic correlation between magnetospheric particle events and earthquakes has been provided. The existence of such a correlation would imply that the electromagnetic and plasma waves emitted by the earthquakes are able to propagate along the magnetic field lines and to interact by resonating with the electrons and positrons (secondary albedo particles) in the inner magnetosphere of the Earth. Only indirect evidence is presented in the above-mentioned documents and, to date, the evidence of a possible correlation has been discussed using completely unsatisfactory statistical analysis.

[0034] One of the main problems of the method of Galper et al. concerns the use of the L shell to locate the geographical regions possibly affected by the seismic events. Traditionally, the regions identified by the above-mentioned method consist of two "bands" almost horizontal in longitude, corresponding to the points where the magnetic field lines intersect the Earth's surface (corresponding to a given L shell), one above the geomagnetic equator and the other below the geomagnetic equator, both extending to the entire circumference of the Earth. This feature generates a great uncertainty on the geographical regions where the seismic events can occur.

[0035] Another main limitation of the method of Galper et al. is the low statistical significance and the large number of false correlations (false positives) resulting from the choice of associating the magnetospheric events with earthquakes having a magnitude with a relatively low threshold (M = 5).

[0036] As regards the magnetic layer anomalies (e.g. TEC- affecting phenomena) that have been proposed as being associated with earthquakes, this evidence has always been proposed as an "ex post" event, without adequately discussing the global context that usually reveals such anomalies, nor mentioning the missing discussion on "false alarm" events. Similar conclusions can be drawn for the results of the DEMETER satellite, which aimed to highlight ionospheric disturbances and / or anomalous electromagnetic signals in the lower magnetic layer.

[0037] Therefore, it can be concluded that, at present, the magnetic layer measurements of the particle bursts that can be associated with earthquakes, the TEC-type anomalies and the ionospheric disturbances that cross the magnetic L shell, at most, constitute indirect evidence that can be associated with earthquakes. Therefore, the investigations based on these hypotheses or based on the methods proposed so far are not based on satisfactory statistical evidence. SUMMARY

[0038] Therefore, there is still felt the need to develop a monitoring method that allows to completely or at least partially overcome the drawbacks and limitations of the methods of the prior art described above. The general purpose of the present description is therefore to provide a monitoring method that allows to meet the needs described above.

[0039] This general purpose is achieved by the monitoring method as generally defined in the present application. Preferred and advantageous embodiments of the monitoring method described above are defined in the present application.

[0040] The application will be better understood with reference to the following detailed description of specific embodiments, provided by way of example and therefore not in any way limiting, with reference to the attached drawings, briefly described in the following paragraphs. BRIEF DESCRIPTION OF DRAWINGS

[0041] Figure 1 A schematic view of a non-limiting embodiment of an example of a system suitable for and configured to implement the method for monitoring particle deposition in the magnetic layer according to the present application is shown.

[0042] Figure 2 A possible embodiment of a particle detector that can be used in the system of Figure 1 is shown.

[0043] Figure 3 A flowchart of a non-limiting embodiment of the method for monitoring particle deposition in the magnetic layer according to the present application is shown.

[0044] Figure 4 Acquired data related to particle deposition in a two-dimensional time- longitude graph are shown.

[0045] Figure 5a A time histogram of the data obtained with the monitoring method according to the present application is shown.

[0046] Figure 5b A time histogram of historical data related to seismic events is shown over the same time period as the map of Figure 5a DETAILED DESCRIPTION

[0047] Figure 1 A non-limiting embodiment of a monitoring system 1, 2 suitable and configured to implement the method 100 for monitoring particle deposition in the magnetosphere according to the present application is shown. Figure 3 A flow chart of one possible exemplary and non-limiting embodiment of the monitoring method 100 described above is shown.

[0048] With reference to Figure 1 The monitoring system 1, 2 comprises a space portion comprising at least one satellite vehicle 1 movable on an orbit 3 with respect to the planet Earth 4, or in short, a man-made satellite 1 or satellite 1. On the satellite vehicle 1, at least one particle detector 10 is installed, which is suitable and configured to detect charged magnetospheric particles, preferably charged particles having a kinetic energy lower than 1 GeV (Giga electron Volt).

[0049] According to an advantageous embodiment, the space portion described above comprises a constellation of satellite vehicles 1, i.e. a plurality of satellite vehicles 1, each of which is installed with a respective particle detector 10.

[0050] The monitoring system 1, 2 comprises at least one ground portion comprising at least one ground station 2 suitable and configured to be operatively connected, directly or indirectly, with the satellite vehicle 1 to receive telemetry data transmitted by the satellite vehicle 1. The ground station 2 comprises, in a per se known manner, satellite data receiving means and one or more processors suitable and configured to process the received data to generate processed data. The aforesaid operative connection can be direct or through other satellite vehicles 1, or in general through space vehicles or space stations. The ground station can comprise a plurality of stations geographically dispersed and operatively connected to each other. The monitoring system 1, 2 preferably comprises a display system (not shown in the figures), for example at least one display, suitable and configured to display the processed data. The display system is for example housed in the ground station 2 or in another station or processing center operatively connected to the ground station 2.

[0051] ​According to a particularly advantageous embodiment, the orbit 3 of the satellite vehicle 1 is an equatorial orbit, preferably a low Earth orbit (LEO). Since the charged particles of interest for the monitoring method 100 according to the application are the charged particles in resonance with the magnetospheric plasma waves (the magnetospheric plasma waves are a physical phenomenon that occurs in an effective way only with particles such as electrons and positrons), several advantages can be obtained by choosing an equatorial LEO orbit with respect to a polar orbit, in particular:

[0052] - in the equatorial LEO orbit, the particle fluxes in the energy range of 0.01 GeV to 0.10 GeV are dominated by electrons and positrons (electrons and positrons should be secondary antishine particles with respect to the primary cosmic rays). At an altitude of about 500 km, the electron and positron fluxes are in the range of 10 3 -10 4 (m 2 ssr GeV) -1 ;

[0053] - the equatorial orbit allows to avoid the background due to the high flux of solar particles, as well as the background caused by the cosmic proton flux in the kinetic energy range lower than 1 GeV;

[0054] - the equatorial orbit is most suitable for acquiring the signal according to the geomagnetic longitude. On the contrary, the polar orbit is not suitable for this purpose, since the polar orbit makes it possible to acquire the signal mainly according to the L shell and not the longitude.

[0055] According to a particularly preferred but not limiting embodiment, the satellite vehicle 1 is for example the satellite known as AGILE, which is described for example in the article "The AGILE Mission" by M. Tavani et al., Astron. & Astrophys., 502, 995-1013 (2009).

[0056] In fact, the AGILE satellite is in a unique condition to study the phenomenon of particle deposition in the inner magnetosphere, since the orbit of the AGILE satellite is not affected by solar storms or external magnetic disturbances. The AGILE satellite is currently orbiting the Earth at an equatorial orbit of about 500 km high. On board the AGILE satellite, a particle detector 10 is installed, in particular an imaging gamma detector (GRID), which, in addition to detecting cosmic gamma rays with energies exceeding 20 MeV, is also able to effectively detect charged magnetospheric particles. This is accurately described, for example, in the article by A. Argan, G. Piano, M. Tavani and A. Trois, "AGILE as a particle detector", Journal Geophys. Res., 121, 3223-3239 (2016), published in 2016. The latter article (in particular regarding the structure and operation of the particle detector GRID) is fully incorporated herein as a reference for describing the structure and operation of a non-limiting example of a particle detector 10 suitable for use in the monitoring method 100 according to the present application.

[0057] As far as the AGILE satellite is concerned, the charged particle flux in the orbit of about 95 minutes is mainly composed of electrons and positrons with kinetic energy lower than 1 GeV. The charged particle detection rate of the particle detector GRID (after crossing the anticoincidence system of the detector described above) is relatively low (a few Hz). The orbit 3 of the AGILE satellite does not undergo transient increases in the number of charged particles caused by solar activity or magnetic disturbances, which instead strongly affect other satellites on inclined or polar orbits.

[0058] As far as the AGILE satellite is concerned, the acceptance of the particle detector GRID for the detection of particles is about 50 cm 2 sr, the instrument response depending on the angle of incidence of the particles with respect to the axis of the particle detector GRID; therefore, the detection of cosmic gamma photons coexists with the effective acquisition of data of charged particle events. These latter events trigger the on-board data acquisition system and are transmitted to the ground station 2 together with precise data, preferably data on the acquisition time, the local magnetic field and the orbital position information.

[0059] Reference is now made to Figure 3 , the monitoring method 100 comprises a step 101 of detecting ("partial_detection") charged magnetospheric particles by means of a particle detector 10 installed on board a satellite vehicle 1 in orbit, associating the detected charged particles with respective detection data.

[0060] As already explained, one possible example of the particle detector 10 is the particle detector GRID mounted on the AGILE satellite, and in this case the particle detector GRID is a gamma-ray imaging detector, which is also used for example to detect charged magnetospheric particles, for example with kinetic energy lower than 1 GeV. In alternative embodiments, the particle detector 10 can be for example a simpler and smaller particle detector, configured for example to detect and track exclusively charged particles.

[0061] According to a general embodiment, the particle detector 10 comprises a particle imaging tracker and / or an imaging calorimeter.

[0062] According to a particularly advantageous embodiment, the particle detector 10 comprises a multi-layer structure 11 or a segmented structure 11, for example comprising a plurality of solid-state planar sub-detectors, for example made of silicon-tungsten, so as to arrange a stack of sub-detectors aligned along the axis z. Each of the above-mentioned sub-detectors allows for example to detect the coordinates x, y of each charged particle on the impact plane, and preferably to detect the amount of charge deposited by the charged particle on the sub-detector. The aforementioned multi-layer structure thus allows to track the path of the charged particle inside the particle detector 10 in three-dimensional space (3D). Charged particles with relatively high kinetic energy can pass through the entire multi-layer structure 11 and affect all the sub-detectors, also depending on the direction; while charged particles with relatively small kinetic energy can stop after impacting one or more of these sub-detectors. In the case of the particle detector GRID mounted on the AGILE satellite, the multi-layer structure 11 is for example made of silicon-tungsten and comprises 16 sub-detectors, each of which is able to detect the coordinates x, y of each charged particle on the impact plane, and preferably to detect the amount of charge deposited by the charged particle on the sub-detector. Figure 2 In the particular example shown corresponding to the particle detector GRID mounted on the AGILE satellite, the particle detector 10 comprises a multi-layer structure 11 and preferably also a calorimeter 12 (for example in cesium iodide), wherein the multi-layer structure 11 is located above the calorimeter 12. The particle detector 10 can for example comprise an anticoincidence screen 13.

[0063] For example, in step 101 of the monitoring method 100, the detection data associated with each charged particle comprise data relating to the path of the charged particle inside the particle detector 10 (for example in 3D), and / or data relating to the amount of charge deposited by the particle in the detector 10, and / or data relating to the time at which the detection of the charged particle occurred, and / or data relating to the geomagnetic longitude at which the detection of the particle occurred.

[0064] The monitoring method 100 further includes step 102 (“Energy_Distribution”), processing the detection data to correlate (i.e., distribute) the detected magnetospheric particles to corresponding kinetic energy estimates or measurements. A kinetic energy estimate or measurement refers to any quantitative data corresponding to or associated with the kinetic energy of a charged particle. This estimate or measurement can be obtained according to various methods known to those skilled in the art, for example, by counting the number of sub-detectors traversed by the charged particle, and / or by analyzing the geometric path of the charged particle in the multilayer structure (e.g., deviation of such path), and / or by measuring the amount of charge deposited by the particle (e.g., on each sub-detector involved), and / or by using data provided by the calorimeter 12 (if available).

[0065] According to an advantageous embodiment, the monitoring method 100 further includes the step of: determining the pitch angle (or angle of arrival) of 103 electromagnetically charged particles relative to a local magnetic field, and selecting (for subsequent processing) particles whose pitch angles fall within one or more pitch angle ranges. Thus, detection events that are absolutely or statistically uninteresting to subsequent processing can be discarded. For example, charged particles whose arrival direction is perpendicular or nearly perpendicular to the local magnetic field can be discarded because charged particles characterized by these arrival directions are statistically not particles undergoing deposition.

[0066] Monitoring method 100 also includes:

[0067] - Get 104(“N”) H The first count value N is obtained in relation to the number of charged particles detected within a time period. H The first count value is associated with a relatively high kinetic energy estimate or kinetic energy measurement value that is included in the first energy range;

[0068] - Get 105("N" L The second count value N, associated with the number of particles detected during the time period, is obtained. L The second count value is associated with a relatively low kinetic energy estimate or kinetic energy measurement value that is included in the second energy range.

[0069] The first energy range and the second energy range can be defined as the high-energy channel and the low-energy channel, respectively.

[0070] According to a particularly advantageous embodiment, a first energy range and a second energy range are selected such that, under normal conditions, the first count value N... H Second count value N L They are equal to each other or approximately equal to each other.

[0071] Conveniently, the first energy range comprises energies greater than 60 MeV and the second energy range comprises energies lower than 40 MeV. Advantageously, the second energy range comprises energies higher than 5 MeV (e.g. higher than 10 MeV) and lower than 40 MeV.

[0072] According to a possible embodiment, the two energy ranges are adjacent to each other and have a common limit value equal to or approximately equal to 50 MeV. For example, the first energy range comprises energies lower than (or lower than / equal to) approximately 55 MeV and the second energy range comprises energies greater than / equal to (or greater than) 55 MeV.

[0073] For the purposes of the present description, when the word "approximately" is associated with a numerical value, it is intended to specify the exact numerical value, as well as a variation value higher or lower than the numerical value by at most 10%.

[0074] Again with reference to Figure 3 , the monitoring method 100 further comprises the following steps:

[0075] - detecting a second count value N L with respect to the first count value N H of the relative variation value 106 ("delta

[0076] _detection");

[0077] - determining 107 ("MPP determination") that a pulse event of the magnetic layer particle deposition - or "MPP event" - has occurred within the time period mentioned above, by comparing the variation value mentioned above with a threshold value.

[0078] From a practical point of view, the MPP event is an event indicative of a pulsed deposition of charged particles due to a resonance phenomenon between the charged particles and a radiation (e.g. a plasma wave propagating in the Earth's magnetosphere). For example, the radiation can be caused by natural and / or unnatural phenomena affecting the Earth's atmosphere and / or lithosphere.

[0079] According to a particularly advantageous embodiment, the threshold value mentioned above is set so as to associate the variation value with historical data relating to seismic or pre-seismic activity events, the historical data relating to seismic or pre-seismic activity events comprising geographical position and intensity information of the events.

[0080] The aforesaid MPP event constitutes an event representative of a pulsed deposition of charged magnetic layer particles with respect to the deposition of charged particles that can be detected in general in the absence of perturbations.

[0081] The aforesaid time range can be of any large or small extent, for example, the time range can have the order of magnitude of one second or of ten seconds.

[0082] According to an advantageous embodiment, the step of detecting the relative change value 106 includes: calculating a first count value N. H Second count value N L Between, or the second count value N L With the first count value N H The operation of the hardness ratio HR. The steps to determine that an MPP event has occurred ("MPP_OK") include: verifying whether the HR is higher than, lower than, or equal to the threshold.

[0083] For example, when HR=N H / N L In this case, the threshold (exceeding which indicates an MPP event has occurred) is greater than or equal to 10; for example, the threshold is approximately 15, or, for example, 14. It has been shown that it is advantageous to select [a threshold] for N. H Value and N L The energy range for counting values ​​is such that, under normal conditions, these values ​​are equal to or approximately equal to each other, thus making HR approximately equal to or about equal to 1.

[0084] According to an advantageous embodiment, the monitoring method 100 further includes the step of eliminating and / or identifying 108 (“false event_discard”) false events that will be associated with the change value detected in the detection step 106 with indicators of magnetosphere and solar activity. Indeed, it is known that certain types of events (e.g., solar storms) can lead to anomalous deposition of electromagnetic particles.

[0085] Monitoring method 100 also includes the following steps:

[0086] - Assign 109 ("Longitude-Time_Assignment") to each MPP event, which represents the geomagnetic longitude and time at which the MPP event occurred;

[0087] - Definition 110 (“Cluster_Definition”) A group or more groups of MPP events, or a cluster of MPP events, each group comprising MPP events occurring within a time range, at the same geomagnetic longitude, or at relatively close geomagnetic longitudes.

[0088] For example, the time range mentioned above is on the order of several weeks, such as 3 to 5 weeks, or 4 weeks.

[0089] For example, relatively close geomagnetic longitudes are longitudes that fall within a range of longitudes with a maximum value of 20° (e.g., equal to or approximately equal to 15° or 10°).

[0090] After the step 110 of defining one or more groups of MPP events, the monitoring method 100 comprises a step of identifying 111 ("Probable Seismo- Precursor Activity_Identification") the group of MPP events or the cluster of MPP events as an indication of natural or unnatural surface activity (e.g. seismo-precursor activity or seismic activity) based on the number of MPP events included in the group of MPP events and / or based on the associated variation value found in the detection step 106. Such number is greater than or equal to 1 and preferably greater than or equal to 2. For example, if a very high HR is associated with a MPP event, it can be determined that the cluster is a degenerate cluster and includes only one MPP event. For MPP events with a lower HR (e.g. equal to 10), it can be confirmed that a group of MPP events must contain a minimum number of events equal to 2, or 3 or 4, in order to be an indication of seismo-precursor or seismic activity. It is noted that the aforementioned activity is not limited to seismic or seismo-precursor activity, since the aforementioned activity can also include other natural activities (e.g. meteorological natural activities such as surface gamma ray flashes) or unnatural activities that can affect particle deposition.

[0091] Preferably, the monitoring method 100 further comprises a step 112 ("Earthquake Alert_Generation") of generating an earthquake or seismo-precursor alert. Said alert can be displayed on a screen, for example, and / or sent through a data message (e.g. a text message or an email).

[0092] For example, in Figure 4 , the MPP events for which the calculated HR (Hardness Ratio) value is greater than or equal to 14 are mapped onto a two-dimensional longitude-time graph. In these MPP events, in fact, there is a significant depletion of the deposition of low-energy charged particles with respect to the deposition of high-energy charged particles. In Figure 4 , the 6 groups of MPP events or clusters identified in the step 111 of the monitoring method 100 have been marked using the respective dashed circles.

[0093] It is noted that the steps of the monitoring method 100 described above can be performed in a different order than the one of the schematic diagram of Figure 3 . For example, the acquisition steps 104 and 105 can be reversed or performed simultaneously. Moreover, it is necessary to perform the detection particles step 101 on board the satellite vehicle 1, while the subsequent processing steps can be performed on the ground after storing the data on board the satellite vehicle 1 and transferring the data acquired in the step 101 to the ground station 2, although the execution of some of said steps on board the satellite vehicle 1 can be advantageous to discard particles and / or MPP events that are not of interest for the subsequent processing steps already on board the satellite, thus reducing the bandwidth resources necessary for the transfer of data to the ground.

[0094] Experimental results

[0095] Experimental results obtained by processing the data acquired by the AGILE satellite by means of a processing system based on a software specifically developed will be described below.

[0096] The focus is on the detection, by the GRID particle detector of the AGILE satellite, of a pulse reduction of the particles detected in the low-energy channel with respect to the particles detected in the high-energy channel, with high statistical significance. The "hardness" is defined as the Hardness Ratio (HR), defined as the number of high-energy events divided by the number of low-energy events, both determined in the same time range δt. The pulse MPP events are defined in terms of the associated Hardness HR in the time range δt. HR(N) is the hardness value associated with the MPP events having a HR value greater than or equal to N. The measured particle count rate in the two energy ranges (and therefore the HR(N) values) is affected by the Poisson statistics and by other possible effects that affect its presence.

[0097] The particle data stream provided by the AGILE satellite along the equatorial orbit constantly provides HR values as a function of time T and geomagnetic longitude LG. In view of the detection capabilities of AGILE, the appropriate bins for analyzing the longitudinal and temporal features of HR are given in time bins of 1 day and in geomagnetic longitude bins of 1 degree. As an example, Figure 4 The longitudinal and temporal distribution of the MPP events measured at HR(14) during the acquisition of the data analyzed (from 16 April 2015 to 30 November 2017) is shown. It is essential to recognize that the MPP event measurements in this case are not affected by solar events or by magnetospheric effects caused by atmospheric flashes. Therefore, the local and global lack of uniformity, which can be seen in the distribution of the MPP events in Figure 4 is not caused by external solar or meteorological effects, or by the characteristics of the particle detector on board the AGILE satellite.

[0098] The processing system developed allows to correlate the distribution of the detected MPP events with the occurrence of earthquakes, i.e. seismic events. The data of interest for this type of seismic analysis (time, geographical position, magnitude and physical parameters of the seismic events) are obtained from the public archives of the United States Geological Survey (USGS). In order to minimize the effects of random statistical fluctuations, this analysis only considers earthquakes with magnitude M>6 (in the MMS scale), with particular emphasis on earthquakes with M>7.

[0099] The processing system has allowed to verify the existence of a "global" temporal correlation between MPP events and earthquakes by considering the total amount of time bars of one hundred days. This choice was motivated by the need to initially check the possible correlation between the apparently random value of MPP events and an amount proportional to the total seismic energy of the most intense earthquakes. To this end, the temporal behavior of two amplitudes was compared. The first amplitude is an amount proportional to the negative of the logarithm of the joint probability of MPP events occurring within a bar of one hundred days, according to the Poisson statistics. The second amplitude is an amount proportional to the negative of the logarithm of the joint probability of earthquakes occurring within the same time bar, assuming that the probability of an earthquake occurring is not correlated with its energy. These amounts are summed over the entire range of longitude (excluding the values in the South Atlantic Anomaly (SAA)) and over a time bar of one hundred days, then these amounts are plotted as histograms of the normalized values of MPP events (HR) and of the cumulative energy of earthquakes (Ψ N ) respectively. Figure 5a and Figure 5b The results of this analysis are shown for HR (14) and for earthquakes of magnitude M > 6 in the northern geomagnetic hemisphere. At first glance, the similarity of the two distributions of MPP events and earthquakes is evident, with the maximum and minimum falling within the same time range. A joint statistical analysis of the two distributions, aimed at testing the hypothesis of the existence of a correlation between the two, provides a Kolmogorov-Smirnov coefficient equal to 0.97 and a Pearson coefficient equal to 0.928.

[0100] As a next step, the geographical localization of MPP events has been taken into account, considering the fact that the value of the geomagnetic longitude L G can be assigned to each MPP event. At this point, MPP events can be mapped into a two-dimensional longitude-time graph and a plurality of groups of MPPs (clusters) including statistically significant MPPs can be identified.

[0101] If a small fraction of the outstanding MPP events is directly related to electromagnetic signals originating from the area affected by an earthquake and transported along the north-south magnetic meridian, then a correlation between these outstanding MPP events and high-intensity earthquakes can be expected, not only in terms of time but also in terms of geomagnetic longitude; these electromagnetic signals propagate along the magnetic field lines (as expected for VLF / ELF and siren waves). Given the statistical data of MPP events and the coverage of the AGILE satellite per unit of longitude and time, a possible correlation between MPP events and earthquakes has been searched for in a circle of radius R D measuring the radius of the area affected by the seismic phenomenon; R DThe study was conducted on a day-week scale over a longitude range given by the magnitude of the earthquake event. For each earthquake, a two-dimensional "active region (AR)" was determined, which is concentrated within a range ΔL' = 2R. D The geomagnetic longitude and the location of the seismic event defined by the time range ΔT'. The amount of this time range is the time delay ΔT = T between the MPP with HR(15) and earthquakes (EQ) occurring in the northern geomagnetic hemisphere within the range ΔL', with magnitudes M≥6.4 and M>7. MPP -T EQ The distribution (using 7-day bars) was determined. Both distributions showed an excessive number of peak events in the first negative time bar (suggesting that a subset of MPP events predicted the earthquake), with asymmetrical amplitudes distributed around the peaks. From the observed distributions, the time range defining the active region was obtained based on a set of three bars preceding the earthquake event and one bar following it. Therefore, the total time range defining the active region is ΔT' = 4 weeks, consisting of three weeks before the EQ and one week after the EQ. A full simulation was performed to determine the statistical significance of this process (see the "Statistical Discussion" section below).

[0102] After defining the regions of seismic events, the active regions are assigned to MPP clusters in the two-dimensional map, thereby identifying these active regions as possible pre-seismic activity (PPA) regions.

[0103] For future events, if significant clustering exceeds the MPP event threshold, the developed processing system generates pre-earthquake warnings by specifying the geomagnetic longitude range, time range, and the probability of observed MPP event clusters occurring.

[0104] The processing system also generates MPP event graphs for different threshold parameters, and these MPP event graphs can be used for electronic transmission (computers and smartphones using dedicated pages / applications).

[0105] Statistical analysis

[0106] MPP events with large hardness ratios (HR) are correlated with the activity areas of large-magnitude earthquakes not only temporally but also geomagnetically in longitude. This paper considers a two-dimensional distribution of MPP events with HR (15) and a two-dimensional distribution of activity areas of earthquakes with magnitude M>7. The first estimate of the random occurrence probability of the similarity between these two distributions is based on the binomial probability p = 2x10 of the observed MPP events overlapping with the activity areas in time and longitude. -8. This value was confirmed by full simulations, as shown below.

[0107] The statistical significance of the results obtained was determined by performing full simulations of the HR signal, reproducing the random fluctuations caused by the Poisson statistics affecting the MPP events. Three conditions were imposed in order to select the cases of interest for the randomly generated distribution. The first condition (C1) is based on the global temporal correlation shown in Figure 5a and Figure 5b : the simulated distribution of MPP events must satisfy the requirement of reproducing a correlation similar to that shown in Figure 5a and Figure 5b . The second condition (C2) is imposed by the two-dimensional distribution: the total number of HR(15) falling within the active area of seismic events of M>7 must be equal to or greater than 17 (determined from observations). The third condition (C3) is imposed by requiring that the number of active areas with at least one HR(15) within them be greater than or equal to 10 out of a total of 13 obtained from observations. From the product of the three conditional probabilities C1-C2-C3, a first estimate of the a priori probability P tot-pre = P(C1,C2,C3) = P(C1)P(C2|C1)P(C3|C1,C2) is obtained.

[0108] Based on the Pearson coefficient values of Figure 5a and Figure 5b , an estimate P(C1) = 7.3 x 10 -5 has been obtained. A binomial estimate of the (unconditional) probability P(C2) = 2 x 10 -8 has also been obtained. Furthermore, P(C3|C1,C2) = 0.22. The product of these probabilities is thus P(C1)P(C2)P(C3|C1,C2) = 3.2 x 10 -13 .

[0109] However, since it is difficult to determine the conditional probability P(C2|C1), only full simulations with a sufficient number of iterations can provide a final value of the total a priori probability P tot-pre . Full simulations were therefore performed with a total number of iterations equal to 6.267 x 10 12 . This simulation produced 25 simulated configuration cases that satisfied the C1-C2-C3 conditions for the case of HR(15) and for the case of EQs of M>7 in the northern geomagnetic hemisphere. As a result of this simulation, the a priori probability for this case is thus P tot-pre = 3.99 x 10 -12 .

[0110] The final probability is obtained by considering the number of trials performed. A conservative estimate of the number of trials is N trial= 2.6 x 10 4 Therefore, the detected distribution has a total probability after a final trial that occurs randomly given by P tot-pre The product with N trial gives P tot-post [HR(15), M > 7] = 1.04 x 10 -7 This value corresponds to a statistical significance greater than 5σ (in units of equivalent standard deviation of a two-sided Gaussian distribution).

[0111] The independent simulation for the case of HR(15) and M > 6.4 earthquakes (6.058 x 10 12 iterations) produced 84 cases that satisfy the conditions C1-C2-C3, and the value P tot-pre = 1.39 x 10 -11 This means that P tot-post [HR(15), M > 6.4] = 3.6 x 10 -7 This value is slightly lower than the significance of 5σ (in units of equivalent standard deviation of a two-sided Gaussian distribution).

[0112] CONCLUSIONS

[0113] From the above it is evident that the monitoring method 100 and the monitoring systems 1, 2 allow to fully achieve the preset purpose of overcoming the drawbacks of the prior art. By analyzing the variation values between the deposition of charged particles in the relatively high-energy channel and the relatively low-energy channel, respectively, if these variation values are considered significant, it is possible to obtain a high correlation between the groups of MPP events and the seismic events of relatively high magnitude (M > 6), thus generating a seismic or pre-seismic alarm.

[0114] With an unprecedented statistical significance, the correlation between MPP events and high-energy earthquakes in the northern geomagnetic hemisphere is established, and the cause of the pulsed deposition of charged particles observed through the described monitoring method can be attributed to the wave-particle resonance in the ELF type electromagnetic wave range. This interpretation is in line with what is expected for electromagnetic waves that must pass through rocks and salt water to propagate in the lithosphere.

[0115] The embodiments and the constructional details can be widely varied with respect to the above described description disclosed by way of non-limiting example, without departing from the scope of the present application as defined in the attached claims, without prejudice to the principles of the present application.

Claims

1. A method (100) for monitoring the deposition of magnetospheric particles, comprising the steps of: - detecting (101) charged magnetospheric particles by means of at least one particle detector (10) installed on at least one satellite vehicle (1) in an orbit (3), associating the detected particles with corresponding detection data; - processing (102) the detection data to associate corresponding kinetic energy estimates or kinetic energy measurements with the detected magnetospheric particles; - obtaining a first count value N related to the number of charged particles detected in a time period H (104), the first count value N H associated with a relatively higher kinetic energy estimate or kinetic energy measurement comprised in a first energy range; - obtaining a second count value N related to the number of charged particles detected in said time period L (105), said second count value N L associated with a relatively lower kinetic energy estimate or kinetic energy measure comprised in a second energy range; - detecting said second count value N L a relative change value (106) with respect to said first count value N H ​ - determining (107) that a pulse event of magnetospheric particle deposition, MPP event, has occurred within the time period, comparing the change value with a threshold value; - assigning (109) to the MPP event the geomagnetic longitude and time at which the MPP event occurred; - defining (110) one or more groups of MPP events, each group of MPP events comprising MPP events occurring within a time range, at the same geomagnetic longitude or at relatively close geomagnetic longitudes; - identifying (111) the group of MPP events as an indication of a surface-originating activity, either a pre-seismic activity or a seismic activity, based on the number of MPP events included in a group of MPP events and / or based on the associated change values found in the detection step (106); 2. The method (100) of claim 1, comprising: - generating (112) a pre-seismic activity alert or a seismic activity alert.

3. The method (100) of claim 1, wherein Said step of detecting a relative variation value (106) comprises the operation of calculating said first count value N H with respect to said second count value N L or the hardness ratio HR of said second count value N L with respect to said first count value N H and said determining step (107) comprises the operation of verifying whether said HR is higher, lower or equal to said threshold value.

4. The method (100) of claim 1, wherein The at least one satellite vehicle (1) is in an equatorial orbit (3).

5. The method (100) of claim 1, comprising: - a step of eliminating and / or identifying (108) false events associating the detected change values with indicators of magnetospheric and solar activity.

6. The method (100) of claim 1, wherein The particle detector (10) allows detecting charged magnetospheric particles, distinguishing them from gamma rays.

7. The method (100) of claim 1, wherein The particle detector (10) comprises a particle imaging tracker and / or an imaging calorimeter.

8. The method (100) of claim 1, wherein The first energy range and the second energy range are chosen such that, under normal conditions, the first count value N H and the second count value N L are equal to or approximately equal to each other.

9. The method (100) of claim 1, wherein The charged magnetospheric particles are electrons.

10. The method (100) of claim 1, wherein The charged magnetospheric particles are positrons.

11. The method (100) of claim 1, wherein The particle detector (10) is suitable for and configured to detect and track particles with energy less than 1 GeV.

12. The method (100) of claim 1, comprising: A step of storing the detection data on the satellite vehicle (1) and a step of transmitting at least part of the detection data, directly or indirectly, to a ground station (2) operatively connected to the satellite vehicle (1).

13. The method (100) of claim 12, comprising: A step of processing the detection data at least partially on the satellite vehicle, and wherein the transmission step comprises transmitting the processed detection data.

14. The method (100) of claim 1, wherein The threshold value is set to associate historical data of the change values and historical data related to seismic events, including geographical location and intensity information of the seismic events.

15. The method (100) of claim 1, further comprising the step of: Determining (103) the pitch angle of the charged magnetospheric particles with respect to the local magnetic field and selecting particles whose pitch angle is included in one or more pitch angle ranges.

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