Searching for cavities of various densities in the Earth's crust with a low-energy electron-antineutrino beta-beam

We propose searching for deep underground cavities of different densities in the Earth's crust using a long-baseline electron-antineutrino disappearance experiment, realized through a low-energy beta-beam with highly-enhanced luminosity. We focus on four cases: cavities with densities close to that of water, iron-banded formations, heavier mineral deposits, and regions of abnormal charge accumulation that have been posited to appear prior to the occurrence of an intense earthquake. The sensitivity to identify cavities attains confidence levels higher than $3\sigma$ and $5\sigma$ for exposures times of 3 months and 1.5 years, respectively, and cavity densities below 1 g cm$^{-3}$ or above 5 g cm$^{-3}$, with widths greater than 200 km. We reconstruct the cavity density, width, and position, assuming one of them known while keeping the other two free. We obtain large allowed regions that improve as the cavity density differs more from the Earth's mean density. Furthermore, we demonstrate that knowledge of the cavity density is important to obtain O(10%) error on the width. Finally, we introduce an observable to quantify the presence of a cavity by changing the orientation of the electron-antineutrino beam, with which we are able to identify the presence of a cavity at the $2\sigma$ to $5\sigma$ C.L.Comment: 7 pages, 5 figures; matches published versio

Irpinia earthquake 23 November 1980 – Lesson from Nature reviled by joint data analysis

A devastating earthquake of magnitude 6.9 occurred in Southern Italy on 23rd November 1980 in Irpinia-Basilicata area. Variations of different geochemical, atmospheric and ionospheric parameters and electromagnetic emissions were registered around the time of the Irpinia earthquake. The substantial progress reached in understanding the physics of the electromagnetic and thermal anomalies associated with the earthquake preparation process permitted us to create the Lithosphere-Atmosphere-Ionosphere (LAI) coupling model published recently. It shows that the observed effects are not independent but present the cause-consequence chain of physical processes and plasma- chemical reactions. We try to analyze the seismic data, radon emanation, hydrological anomalies, ground based ionosondes network, NOAA/AVHRR Thermal Infrared Irradiance (TIR) anomaly, Intercosmos-19 satellite topside sounding and VLF emissions data using the concept of the developed model and existing laboratory and largescale active experiments on air ionization. If the observed radon activity is really connected with the earthquake preparation process, all other variations of the atmosphere and ionosphere parameters can be explained as a consequence of the main physical process – air ionization by radon

Space-borne Observations of Atmospheric Pre-Earthquake Signals in Seismically Active Areas: Case Study for Greece 2008-2009

We are conducting theoretical studies and practical validation of atm osphere/ionosphere phenomena preceding major earthquakes. Our approach is based on monitoring of two physical parameters from space: outgoi ng long-wavelength radiation (OLR) on the top of the atmosphere and e lectron and electron density variations in the ionosphere via GPS Tot al Electron Content (GPS/TEC). We retrospectively analyzed the temporal and spatial variations of OLR an GPS/TEC parameters characterizing the state of the atmosphere and ionosphere several days before four m ajor earthquakes (M>6) in Greece for 2008-2009: M6.9 of 02.12.08, M6. 2 02.20.08; M6.4 of 06.08.08 and M6.4 of 07.01.09.We found anomalous behavior before all of these events (over land and sea) over regions o f maximum stress. We expect that our analysis reveal the underlying p hysics of pre-earthquake signals associated with some of the largest earthquakes in Greece

Atmospheric and ionospheric coupling phenomena related to large earthquakes

This paper explores multi-instrument space-borne observations in order to validate physical concepts of Lithosphere-Atmosphere-Ionosphere Coupling (LAIC) in relation to major seismic events. In this study we apply already validated observation to identify atmospheric and ionospheric precursors associated with some of recent most destructive earthquakes: M8.6 of March 25, 2005 and M8.5 September 15, 2007 in Sumatra, and M7.9 May 12, 2008 in Wenchuan, China. New investigations are also presented concerning these three earthquakes and for the M7.3 March 2008 in the Xinjiang-Xizang border region, China (the Yutian earthquake). It concerns the ionospheric density, the Global Ionospheric Maps (GIM) of the Total Electron Content (TEC), the Thermal Infra-Red (TIR) anomalies, and the Outgoing Longwave Radiation (OLR) data. It is shown that all these anomalies are identified as short-term precursors, which can be explained by the LAIC concept proposed by Pulinets and Ouzounov (2011)

Atmospheric and ionospheric coupling phenomena associated with large earthquakes

This paper explores multi-instrument space-borne observations in order to validate physical concepts of Lithosphere-AtmosphereIonosphere Coupling (LAIC) in relation to a selection of major seismic events. In this study we apply some validated techniques to observations in order to identify atmospheric and ionospheric precursors associated with some of recent most destructive earthquakes: M8.6 of March 28, 2005 and M8.5 of Sept. 12, 2007 in Sumatra, and M7.9 of May 12, 2008 in Wenchuan, China. New investigations are also presented concerning these three earthquakes and for the M7.2 of March 2008 in the Xinjiang-Xizang border region, China (the Yutian earthquake). It concerns the ionospheric density, the Global Ionospheric Maps (GIM) of the Total Electron Content (TEC), the Thermal InfraRed (TIR) anomalies, and the Outgoing Longwave Radiation (OLR) data. It is shown that all these anomalies are identified as short-term precursors, which can be explained by the LAIC concept proposed in [S. Pulinets, D. Ouzounov, J. Asian Earth Sci. 41, 371 (2011)]

Earthquake Forecast via Neutrino Tomography

We discuss the possibility of forecasting earthquakes by means of (anti)neutrino tomography. Antineutrinos emitted from reactors are used as a probe. As the antineutrinos traverse through a region prone to earthquakes, observable variations in the matter effect on the antineutrino oscillation would provide a tomography of the vicinity of the region. In this preliminary work, we adopt a simplified model for the geometrical profile and matter density in a fault zone. We calculate the survival probability of electron antineutrinos for cases without and with an anomalous accumulation of electrons which can be considered as a clear signal of the coming earthquake, at the geological region with a fault zone, and find that the variation may reach as much as 3% for $\bar \nu_e$ emitted from a reactor. The case for a $\nu_e$ beam from a neutrino factory is also investigated, and it is noted that, because of the typically high energy associated with such neutrinos, the oscillation length is too large and the resultant variation is not practically observable. Our conclusion is that with the present reactor facilities and detection techniques, it is still a difficult task to make an earthquake forecast using such a scheme, though it seems to be possible from a theoretical point of view while ignoring some uncertainties. However, with the development of the geology, especially the knowledge about the fault zone, and with the improvement of the detection techniques, etc., there is hope that a medium-term earthquake forecast would be feasible.Comment: 6 pages, 4 figures, 1 tabl

Tropospheric and ionospheric anomalies induced by volcanic and saharan dust events as part of geosphere interaction phenomena

In this work, we assessed the possible relation of ionospheric perturbations observed by Detection of Electro-Magnetic Emissions Transmitted from Earthquake Regions (DEMETER), Global Positioning System total electron content (GPS TEC), National Oceanic and Atmospheric Administration (NOAA)-derived outgoing longwave-Earth radiation (OLR), and atmospheric chemical potential (ACP) measurements, with volcanic and Saharan dust events identified by ground and satellite-based medium infrared/thermal infrared (MIR/TIR) observations. The results indicated that the Mt. Etna (Italy) volcanic activity of 2006 was probably responsible for the ionospheric perturbations revealed by DEMETER on 4 November and 6 December and by GPS TEC observations on 4 November and 12 December. This activity also affected the OLR (on 26 October; 6 and 23 November; and 2, 6, and 14 December) and ACP (on 31 October-1 November) analyses. Similarly, two massive Saharan dust episodes, detected by Robust Satellite Techniques (RST) using Spinning Enhanced Visible and Infrared Imager (SEVIRI) optical data, probably caused the ionospheric anomalies recorded, based on DEMETER and GPS TEC observations, over the Mediterranean basin in May 2008. The study confirmed the perturbing effects of volcanic and dust events on tropospheric and ionospheric parameters. Further, it demonstrated the advantages of using independent satellite observations to investigate atmospheric phenomena, which may not always be well documented. The impact of this increased detection capacity in reducing false positives, in the framework of a short-term seismic hazard forecast based on the study of ionospheric and tropospheric anomalies, is also addressed

A combined estimator using TEC and b-value for large earthquake prediction

[EN] Ionospheric anomalies have been shown to occur a few days before several large earthquakes. The published works normally address examples limited in time (a single event or few of them) or space (a particular geographic area), so that a clear method based on these anomalies which consistently yields the place and magnitude of the forthcoming earthquake, anytime and anywhere on earth, has not been presented so far. The current research is aimed at prediction of large earthquakes, that is with magnitude M-w 7 or higher. It uses as data bank all significant earthquakes occurred worldwide in the period from January 1, 2011 to December 31, 2018. The first purpose of the research is to improve the use of ionospheric anomalies in the form of TEC grids for earthquake prediction. A space-time TEC variation estimator especially designed for earthquake prediction will show the advantages with respect to the use of simple TEC values. Further, taking advantage of the well-known predictive abilities of the Gutenberg-Richter law's b-value, a combined estimator based on both TEC anomalies and b-values will be designed and shown to improve prediction performance even more.Baselga Moreno, S. (2020). A combined estimator using TEC and b-value for large earthquake prediction. Acta Geodaetica et Geophysica Hungarica. 55(1):63-82. https://doi.org/10.1007/s40328-019-00281-5S6382551Abordán A, Szabó NP (2018) Metropolis algorithm driven factor analysis for lithological characterization of shallow marine sediments. Acta Geod Geophys 53:189–199. https://doi.org/10.1007/s40328-017-0210-zAkhoondzadeh M, Saradjian MR (2011) TEC variations analysis concerning Haiti (January 12, 2010) and Samoa (September 29, 2009) earthquakes. Adv Space Res 47(1):94–104. https://doi.org/10.1016/j.asr.2010.07.024Asencio-Cortés G, Morales-Esteban A, Shang X, Martínez-Álvarez F (2018) Earthquake prediction in California using regression algorithms and cloud-based big data infrastructure. Comput Geosci 115:198–210. https://doi.org/10.1016/j.cageo.2017.10.011Baselga S (2018) Fibonacci lattices for the evaluation and optimization of map projections. Comput Geosci 117:1–8. https://doi.org/10.1016/j.cageo.2018.04.012Baselga S (2019) TestGrids: evaluating and optimizing map projections. J Surv Eng 144(3):04019004Berényi KA, Barta V, Kis Á (2018) Midlatitude ionospheric F2-layer response to eruptive solar events-caused geomagnetic disturbances over Hungary during the maximum of the solar cycle 24: a case study. Adv Space Res 61(5):1230–1243. https://doi.org/10.1016/j.asr.2017.12.021Biswas A, Sharma SP (2017) Interpretation of self-potential anomaly over 2-D inclined thick sheet structures and analysis of uncertainty using very fast simulated annealing global optimization. Acta Geod Geophys 52:439–455. https://doi.org/10.1007/s40328-016-0176-2Borgohain JM, Borah K, Biswas R, Bora DK (2018) Seismic b-value anomalies prior to the 3rd January 2016, Mw = 6.7 Manipur earthquake of northeast India. J Asian Earth Sci 154:42–48. https://doi.org/10.1016/j.jseaes.2017.12.013Buonsanto M (1999) Ionospheric storms—a review. Space Sci Rev 88:563–601. https://doi.org/10.1023/A:1005107532631Buskirk RE, Frohlich CL, Latham GV (1981) Unusual animal behavior before earthquakes: a review of possible sensory mechanisms. Rev Geophys 19:247–270. https://doi.org/10.1029/RG019i002p00247Dobrovolsky IR, Zubkov SI, Myachkin VI (1979) Estimation of the size of earthquake preparation zones. Pure appl Geophys 117:1025–1044. https://doi.org/10.1007/BF00876083Dogan U, Ergintav S, Skone S, Arslan N, Oz D (2011) Monitoring of the ionosphere TEC variations during the 17th August 1999 Izmit earthquake using GPS data. Earth Planets Space 63(12):1183–1192. https://doi.org/10.5047/eps.2011.07.020Florido E, Martínez-Álvarez F, Morales-Esteban A, Reyes J, Aznarte-Mellado JL (2015) Detecting precursory patterns to enhance earthquake prediction in Chile. Comput Geosci 76:112–120. https://doi.org/10.1016/j.cageo.2014.12.002Florido E, Asencio-Cortés G, Aznarte JL, Rubio-Escudero C, Martínez-Álvarez F (2018) A novel tree-based algorithm to discover seismic patterns in earthquake catalogs. Comput Geosci 115:96–104. https://doi.org/10.1016/j.cageo.2018.03.005Freund FT, Kulahci IG, Cyr G, Ling J, Winnick M, Tregloan-Reed J, Freund MM (2009) Air ionization at rock surfaces and pre-earthquake signals. J Atmos Sol Terr Phys 71(17–18):1824–1834. https://doi.org/10.1016/j.jastp.2009.07.013Gopinath S, Prince PR (2018) Nonextensive and distance-based entropy analysis on the influence of sunspot variability in magnetospheric dynamics. Acta Geod Geophys 53:639–659. https://doi.org/10.1007/s40328-018-0235-yGrant RA, Halliday T (2010) Predicting the unpredictable; evidence of pre-seismic anticipatory behaviour in the common toad. J Zool 281:263–271. https://doi.org/10.1111/j.1469-7998.2010.00700.xGrant RA, Halliday T, Balderer WP, Leuenberger F, Newcomer M, Cyr G, Freund FT (2011) Ground water chemistry changes before major earthquakes and possible effects on animals. Int J Environ Res Public Health 8:1936–1956. https://doi.org/10.3390/ijerph8061936Guo J, Yu H, Li W, Liu X, Kong Q, Zhao C (2017) Total electron content anomalies before Mw 6.0 + earthquakes in the seismic zone of southwest China between 2001 and 2013. J Test Eval 45(1):131–139. https://doi.org/10.1520/JTE20160032International GNSS Service (2019) IGS products. https://www.igs.org/products. Accessed 5 May 2019Kane RP (2005) Ionospheric foF2 anomalies during some intense geomagnetic storms. Ann Geophys 23:2487–2499. https://doi.org/10.5194/angeo-23-2487-2005Kulhanek O, Persson L, Nuannin P (2018) Variations of b-values preceding large earthquakes in the shallow subduction zones of Cocos and Nazca plates. J South Am Earth Sci 82:207–214. https://doi.org/10.1016/j.jsames.2018.01.005Lin JW (2010) Ionospheric total electron content (TEC) anomalies associated with earthquakes through Karhunen–Loéve Transform (KLT). Terr Atmos Ocean Sci 21(2):253–265. https://doi.org/10.3319/TAO.2009.06.11.01(T)Lin JW (2011) Latitude-time total electron content anomalies as precursors to Japan’s large earthquakes associated with principal component analysis. Int J Geophys. https://doi.org/10.1155/2011/763527Liu JY, Chen YI, Chuo YJ, Chen CS (2006) A statistical investigation of preearthquake ionospheric anomaly. J Geophys Res 111:A05304. https://doi.org/10.1029/2005JA011333Liu JY, Chen YI, Chen CH, Liu CY, Chen CY, Nishihashi M, Li JZ, Xia YQ, Oyama KI, Hattori K, Lin CH (2009) Seismoionospheric GPS total electron content anomalies observed before the 12 May 2008 Mw7.9 Wenchuan earthquake. J Geophys Res 114:A04320. https://doi.org/10.1029/2008JA013698Nuannin P, Kulhanek O, Persson L (2005) Spatial and temporal b value anomalies preceding the devastating off coast of NW Sumatra earthquake of December 26, 2004. Geophys Res Lett 32:L11307. https://doi.org/10.1029/2005GL022679Pardalos PM, Romeijn HE (eds) (2002) Handbook of global optimization, vols. 1 & 2. Kluwer, DordretchPaul B, De BK, Guha A (2018) Latitudinal variation of F-region ionospheric response during three strongest geomagnetic storms of 2015. Acta Geod Geophys 53:579–606. https://doi.org/10.1007/s40328-018-0221-4Pulinets S, Boyarchuk K (2004) Ionospheric precursors of earthquakes. Springer, BerlinPulinets SA, Legen’ka AD, Gaivoronskaya TV, Depuev VKh (2003) Main phenomenological features of ionospheric precursors of strong earthquakes. J Atmos Sol Terr Phys 65:1337–1347. https://doi.org/10.1016/j.jastp.2003.07.011Reyes J, Morales-Esteban A, Martínez-Álvarez F (2013) Neural networks to predict earthquakes in Chile. Appl Soft Comput 13:1314–1328. https://doi.org/10.1016/j.asoc.2012.10.014Şentürk E, Çepni MS (2018a) A statistical analysis of seismo ionospheric TEC anomalies before 63 Mw ≥ 5.0 earthquakes in Turkey during 2003–2016. Acta Geophys 66:1495–1507. https://doi.org/10.1007/s11600-018-0214-2Şentürk E, Çepni MS (2018b) Ionospheric temporal variations over the region of Turkey: a study based on long-time TEC observations. Acta Geod Geophys 53:623–637. https://doi.org/10.1007/s40328-018-0233-0Şentürk E, Çepni MS (2019) Performance of different weighting and surface fitting techniques on station-wise TEC calculation and modified sine weighting supported by the sun effect. J Spat Sci 64(2):209–220. https://doi.org/10.1080/14498596.2017.1417169Şentürk E, Livaoğlu H, Çepni MS (2019) A comprehensive analysis of ionospheric anomalies before the mw 7.1 Van earthquake on 23 October 2011. J Navig 72(3):702–720. https://doi.org/10.1017/S0373463318000826Shiuly A, Roy N (2018) A generalized VS–N correlation using various regression analysis and genetic algorithm. Acta Geod Geophys 53:479–502. https://doi.org/10.1007/s40328-018-0220-5U.S. Geological Survey (2019) Earthquake catalog. https://earthquake.usgs.gov/earthquakes/search/. Accessed 5 May 2019Warwick JW, Stoker C, Meyer TR (1982) Radio emission associated with rock fracture: possible application to the Great Chilean Earthquake of May 22, 1960. J Geophys Res Solid Earth 87:2851–2859. https://doi.org/10.1029/JB087iB04p02851Yao Y, Chen P, Wu H, Zhang S, Peng W (2012) Analysis of ionospheric anomalies before the 2011 M w 9.0 Japan earthquake. Chin Sci Bull 57(5):500–510. https://doi.org/10.1007/s11434-011-4851-yZakharenkova IE, Shagimuratov II, Krankowski A (2007a) Features of the ionosphere behavior before the Kythira 2006 earthquake. Acta Geophys 55(4):524–534. https://doi.org/10.2478/s11600-007-0031-5Zakharenkova IE, Shagimuratov II, Krankowski A, Lagovsky AF (2007b) Precursory phenomena observed in the total electron content measurements before great Hokkaido earthquake of September 25, 2003 (M = 8.3). Stud Geophys Geod 51(2):267–278. https://doi.org/10.1007/s11200-007-0014-