Multiparametric and multilayer investigation of global earthquakes in the World by a statistical approach
- 1College of Instrumentation and Electrical Engineering, Jilin University, Changchun, China (dedalomarchetti@jlu.edu.cn)
- 2Istituto Nazionale di Geofisica e Vulcanologia, Rome, Italy (dario.sabbagh@ingv.it)
- 3Instituto de Geociencias IGEO (CSIC-UCM), Madrid, Spain (saioa.arquero@igeo.ucm-csic.es)
- 4Universidad Complutense de Madrid - UCM, Madrid, Spain (sdarcang@ucm.es)
- 5Space Observation Research Center, National Institute of Natural Hazards, MEMC, Beijing, China (shenxh@seis.ac.cn)
- *A full list of authors appears at the end of the abstract
Earthquake prediction has always been a challenging task, and some researchers have proposed that it is an even impossible goal, concluding earthquakes are unpredictable events. Such a conclusion seems too extreme and in contrast with several pieces of evidence of alterations recorded by several instrumentations from the ground, atmosphere, and more recently by Earth Observation satellite. On the other side, it is clear that searching the “perfect precursor parameter” doesn’t seem to be a good way, since the earthquake process is a complex phenomenon. In fact, a precursor that works for one earthquake does not necessarily work for the next one, even on the same fault. In some cases, another problem for precursors identification is the recurrency time between the earthquakes, which could be very long and, in such cases, we don’t have comparable observations of earthquakes generated by the same fault system.
In past years, we concentrated mainly on two aspects: statistical and single case study; the first one consists of some statistical evidence on ionospheric disturbances possibly related to M5.5+ earthquakes (e.g., presented at EGU2018-9468, and published by De Santis et al., Scientific Report, 2019), furthermore, some clear signals in the atmosphere statistically preceded the occurrence of M8+ events (e.g., presented at EGU2020-19809). On the other side, we also investigated about 20 earthquakes that occurred in the last ten years, some of them by a very detailed and multiparametric investigation, like the M7.5 Indonesia earthquake (presented at EGU2019-8077 and published by Marchetti et al., JAES, 2020), or the Jamaica earthquake investigation presented at the last EGU2021-15456. We found that both approaches are very important. Actually, the statistical studies can provide proofs that at least some of the detected anomalies seem to be related to the earthquakes, while the single case studies permit us to explore deeply the details and the possible connections between the geolayers (lithosphere, atmosphere and ionosphere).
In this presentation, we want to show an update of the statistical study of the atmosphere and ionosphere, together with a new statistical investigation of the seismic acceleration before M7.5+ global earthquakes.
Finally, we demonstrate that it is essential to consider the earthquake not as a point source (that is the basic approximation), but in all its complexity, including its focal mechanism, fault rupture length and even other seismological constraints, in order to try to better understand the preparation phase of the earthquakes, and the reasons for their different behaviour. These studies give hope and fundamental (but not yet sufficient) tools for the possible achievement, one day, of earthquakes prediction capabilities.
Zhu Kaiguang, Marchetti Dedalo, Chen Wenqi, He Xiaodan, Wang Ting, Wen Jiami, Zhang Donghua, Zhang Hanshuo, Zhang Yiqun
How to cite: Marchetti, D., Zhu, K., De Santis, A., Campuzano, S. A., Zhang, D., Soldani, M., Wang, T., Cianchini, G., D’Arcangelo, S., Di Mauro, D., Ippolito, A., Nardi, A., Orlando, M., Perrone, L., Piscini, A., Sabbagh, D., Shen, X., Zhima, Z., and Zhang, Y. and the Zhu Kaiguang's earthquake research group in Jilin University: Multiparametric and multilayer investigation of global earthquakes in the World by a statistical approach, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3337, https://doi.org/10.5194/egusphere-egu22-3337, 2022.