NH003-0007
Systematic worldwide analysis of physical and chemical atmospheric parameters before the largest earthquakes in the last four decades

Monday, 7 December 2020
Poster
Dedalo Marchetti1,2, Angelo De Santis1, Maurizio Soldani1, Alessandro Piscini3, Saioa A. Campuzano1,4, Gianfranco Cianchini3, Claudio Cesaroni1, Domenico Di Mauro1, Martina Orlando1, Loredana Perrone1 and Dario Sabbagh1, (1)Istituto Nazionale di Geofisica e Vulcanologia, Rome, Italy, (2)Jilin University, College of Instrumentation & Electrical Engineering, Jilin, China, (3)Istituto Nazionale di Geofisica e Vulcanologia, Palermo, Italy, (4)Instituto de Geociencias (CSIC-UCM), Madrid, Spain
Abstract:
A correlation between Swarm satellites electromagnetic anomalies and earthquakes was successfully found, providing some statistical evidence for such perturbations in ionosphere before the occurrence of M5.5+ earthquakes (De Santis et al., 2019, https://doi.org/10.1038/s41598-019-56599-1).

In this study, we extended this approach to atmospheric data retrieved from climatological datasets. The importance of studying the atmosphere together with the ionosphere, is underlined by the vision presented in De Santis et al., 2019, https://doi.org/10.3390/e21040412, called “Geosystemics”.

In this study, we analysed surface air temperature, aerosol, SO2, carbon monoxide and other physical and chemical parameters the occurrence of M8+ earthquakes in the last forty years worldwide (more than 30 events).

To define an anomaly, we calculate the mean and standard deviation of the “historical time series” of the investigated parameter based on the whole dataset, excluding the year of the earthquake. If the value in the earthquake year exceeds the mean over a given threshold, typically two standard deviations of the historical time series, we define it as anomalous.

Most of the studied parameters show a pattern and/or concentration of anomalies that precede from weeks to months the occurrence of the M8+ earthquakes from 1980 to 2017. Furthermore, we notice that at a particular time, most of the investigated parameters show anomalies before 40% to 70% of the studied events.

This result paves the way for the prediction of the most significant seismic events of the world, although most of the time, these anomalies occur without being followed by earthquakes (“false alarms”). This kind of study is necessary for a future prediction system, but it is not yet sufficient, as a significant improvement is needed by means of the integration with many other geophysical investigations (seismic, ground multiparametric stations, ionospheric data and more) within a multiparametric approach.

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