GNGTS 2021 - Atti del 39° Convegno Nazionale

197 GNGTS 2021 S essione 2.1 that energy can be efficiently transferred from magnetic pulses producing electron pitch angle disturbances (Galper et al., 1995). Additionally, the proposed strip of diffuse current, which is able to produce low intensities of magnetic inductions on the Earth’s surface, even if measurable both near and far from the earthquake epicenter, is able to produce significant fields also far from the ground, see Figure 2. Imagine the presence of a magnetometer network distributed on several islands of the West Pacific, where strong earthquakes are correlated with electron bursts having G EB = 3. Although not still existent, this network is currently achievable. Suppose that it exists and is able to obtain a G MF = 1.6 for earthquakes within a certain distance around the stations, with a time advance of magnetic fluctuations of 4 - 6 hours with respect to earthquakes. Then, can be demonstrated that G EB ∪ MF = {G EB P(EB)+[G MF –G EB ∩ MF P(EB|MF)]P(MF)}/{P(EB)+[1 – P(EB|MF)]P(MF)} , (3) where G EB ∩ MF = 1 + cov(EQ,EB ∩ MF)/P(EQ)P(EB ∩ MF) is due to the observation of both EB and MF that are correlated between them, while the covariance can be explicated throughout the histogram of the EQ to EB ∩ MF coincidences Σ {EQ;EB ∩ MF} [EQ × (EB ∧ MF)] , and considering the total number N EB ∩ MF of correlated precursors events. Finally, P(EB|MF) can be calculated through the corr(EB,MF) using observational data. Supposed P(MF) = 0.05, which means 324 magnetic pulses, or sets of magnetic pulses, considered as magnetic alarms on the same time interval as for electron bursts. P(EB|MF) depends on the histogram maximum max Δt* [Σ {EB;MF} (EB × MF)] , where Δt* = 4(6) – Δt is such that the total time in advance of MF s with respect to EQ s is 4 - 6 hours. This could be chosen in the range from 0, no correlation, to 324, the complete correlation being the N EB a much higher number, in order to consider a range of possibility. Concerning G EB ∩ MF , the correlation between EQ s and EB ∩ MF s would need to be calculated utilizing observational data for max Δt [Σ {EQ;EB ∩ MF} (EQ × (EB ∧ MF))] . The dependence between EB s and MF s can be introduced in (3) by fixing a time shift of Δt* so that the number of correlation events max Δt [Σ {EB;MF} (EB × MF)] = max Δt* [Σ {EB;MF} (EB × MF)] . It would be necessary also in this case to consider a range of possibility from 0, no correlation between EQ s and EB ∩ MF s, to 10 common events. The probability gain improvements obtainable thanks to a magnetometer network added to the NOAA satellite during the same time interval are reported in the contour plot of Figure 3. This methodology is general enough so it could be adapted to the combinations of both from Earth’s surface and from space observations, such as electromagnetic, seismic or other physical observable. References Aki, K. (1981). A probabilistic synthesis of precursory phenomena, in Earthquake Prediction , An International Review, Maurice Ewing Vol. 4, pp. 566-574, eds Simpson, D.W. & Richards, P.G., AGU, Washington, DC. Aleksandrin, S. Yu., Galper, A. M., Koldashov, S. V., et al. (2003). High-energy Charged Particle Bursts in the Near-Earth Space as Earthquake Precursors . Annales Geophysicae 21, 597-602. Console, R. (2001). Testing Earthquake forecast hypotheses . Tectonophysics 338, 261-268. Fidani, C., Battiston, R., and Burger, W. J. (2010). A study of the correlation between earthquakes and NOAA satellite energetic particle bursts . Remote Sens. 2, 2170–2184. Fidani, C., Battiston, R., Burger, W. J., and Conti, L. (2012). A study of NOAA particle flux sensitivity to solar activity and strategies to search for correlations among satellite data and earthquake phenomena . Int. J. Remote Sensing 33 (15), 4796-4814. http://dx.doi.org/10.1080/01431161.2011.638337 Fidani, C. (2015). Particle precipitation prior to large earthquakes of both the Sumatra and Philippine Regions: A statistical analysis , J. Asian Earth Sci. 114, 384–392. Fidani, C. (2020). Probability, Causality and False Alarms using Correlations Between Strong Earthquakes and NOAA High Energy Electron Bursts . Ann. Geophys. 63(5), 543. doi:10.44101/ag-7957 Fidani, C., Orsini, M., Iezzi, G., Vicentini, N. and Stoppa, F. (2020). Electric and Magnetic Recordings by Chieti CIEN Station During the Intense 2016-2017 Seismic Swarms in Central Italy . Front. Earth Sci. 8:536332. doi: 10.3389/feart.2020.536332