ORCID Profile
0000-0002-5457-3379
Current Organisation
Jilin University
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Publisher: Elsevier BV
Date: 02-2020
Publisher: MDPI AG
Date: 05-04-2020
DOI: 10.3390/RS12071166
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.
Publisher: Springer Science and Business Media LLC
Date: 25-02-2019
Publisher: Elsevier BV
Date: 07-2019
Publisher: Copernicus GmbH
Date: 23-03-2020
DOI: 10.5194/EGUSPHERE-EGU2020-19809
Abstract: & & Applying a multi-parametric approach, we already investigated the preparatory phase of several medium and large (M6.0 ~ M8.3) earthquakes occurred in the last 6 years in different locations in the World. In some cases, a chain of processes from the lithosphere to atmosphere and ionosphere has been successfully detected (e.g. M7.8 Ecuador 2016: Akhoondzadeh, 2018, ASR, 0.1016/j.asr.2017.07.014 Italian seismic sequence (M6.5) 2016-2017: Marchetti et al., 2019, RSoE, 0.1016/j.rse.2019.04.033 M7.5 Indonesia 2018: Marchetti et al., 2019, JAES, 0.1016/j.jseaes.2019.104097). These analyses underline the importance to study all the & #8220 spheres& #8221 that surround the Earth as suggested by a Geosystemic approach (De Santis et al., 2019, Entropy, 0.3390/e21040412). To analyse the anomalies that occur in the atmosphere we typically calculate the mean and standard deviation of the & #8220 historical time series& #8221 of the investigated parameter based on around 40 years of data, and then we superpose the value of the same quantity in the earthquake year. If the value overpasses two standard deviations of the historical time series, we define this day arameter as anomalous. Applying the same methodology presented in previous works that studied climatological parameters such as skin temperature, total column water vapour, aerosols, and SO& sub& & /sub& , which & sub& & & /sub& seem to provide anomalies possibly related to the earthquake preparation phase (e.g. Piscini et al., 2017, PAGeoph, 0.1007/s00024-017-1597-8), here we investigate more atmospheric parameters proposed as possible precursors in the Lithosphere Atmosphere Ionosphere Coupling (LAIC) models (Pulinets and Ouzounov, 2011, JAES, 0.1016/j.jseaes.2010.03.005) such as methane and surface concentration of carbon monoxide. Other parameters, such as dimethylsulfide could be useful in other geophysical events, such as the volcano eruptions (Piscini et al. PAGeoph 2019, 0.1007/s00024-019-02147-x).& & & & In this study, we also apply a Worldwide Statistical Correlation (WSC), as it was successfully applied to Swarm satellites electromagnetic anomalies and earthquakes, providing some statistical evidence for such perturbations in ionosphere before the occurrence of M5.5+ earthquakes (De Santis et al., 2019, Sci. Rep., 0.1038/s41598-019-56599-1).& & & & The statistical approaches applied to these climatological data, provided by meteorological agencies such as ECMWF and NOAA, provides some interesting concentrations of atmospheric anomalies, preceding from days to several weeks the occurrence of the largest earthquakes from 1980 to 2017.& & & & The study of several chemical and physical (e.g. aerosol particles) components in the atmosphere, the involved physical processes, the chemical reactions and chemical constraints (such as the elements lifetime and interactions in the atmosphere) can help to distinguish which LAIC model is more reliable to produce the observed anomalies before the occurrence of a large earthquake.& & & & & & &
Location: China
No related grants have been discovered for Dedalo Marchetti.