Remote Sensing of Environment | 2019

Pre-earthquake chain processes detected from ground to satellite altitude in preparation of the 2016–2017 seismic sequence in Central Italy

 
 
 
 
 
 
 

Abstract


Abstract This work is based on the retrospective analysis of several geophysical observations to search for possible lithosphere-atmosphere-ionosphere coupling effects in the preparatory phase of the Central Italy seismic sequence 2016–2017. The major seismic events occurred on 24 August 2016 (Mw 6.0 Amatrice earthquake), 30 October 2016 (Norcia mainshock, Mw\u202f6.5) and on 18 January 2017 (four M5+ events close to Campotosto-Montereale). The work consists of a multi parametric approach over different observables from ground and space: the geomagnetic field (from satellites and observatories), atmospheric chemical/physical composition, with the comparison with other already published results from chemistry of groundwater and seismicity. In particular, we investigated the vector magnetic data from INGV ground L Aquila and Duronia magnetic Observatories and ESA Swarm three-satellite constellation. In addition, we searched for anomalies in physical/chemical composition of the atmosphere using MERRA-2 climatological dataset over Central Italy before the start of the seismic sequence. Two anomalous conditions anticipating the seismic sequence by about 275 and 85\u202fdays from geomagnetic Observatories and by about 240\u202fdays from satellite have been found. Furthermore, two highly perturbed periods in atmosphere chemical/physical composition that precede by 200 and 150\u202fdays the start of seismic sequence have been discovered. A comparison with also other published papers results to validate and integrate our findings is finally presented. We find a chain of some quasi synchronous anomalies and propose a global point of view demonstrating that the earthquake preparation phase affects the equilibrium of the Earth system producing anomalies from around a year in lithosphere, atmosphere and ionosphere.

Volume 229
Pages 93-99
DOI 10.1016/J.RSE.2019.04.033
Language English
Journal Remote Sensing of Environment

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