Anomalous seismo-LAI variations potentially associated with the 2017 Mw = 7.3 Sarpol-e Zahab (Iran) earthquake from Swarm satellites, GPS-TEC and climatological data. Issue 1 (1st July 2019) - Akhoondzadeh, Mehdi
Highlights: The Mw = 7.3 earthquake near the Iran-Iraq border in west Iran occurred in 12.11.2017. Median, Kalman filter and NN were implemented to investigate TEC measurements. Swarm data analysis identifies anomalies 8–11 days prior to the earthquake. Climatological data analysis identifies anomalies that precede ionospheric anomalies. The sequence of different anomalies confirms a bottom-up LAIC process. Abstract: The Mw = 7.3 earthquake near the Iran-Iraq border in west Iran (34.911°N, 45.959°E) occurred at 18:18:17 UTC (LT = UTC + 03:30), November 12, 2017 as the result of oblique-thrust faulting at mid-crustal depth (∼19 km). Median, Kalman filter and Neural Network, as three standard, classical and intelligent methods, have been implemented to investigate three months of GPS Total Electron Content (TEC) measurements and to detect the striking anomalous variations around the time and location of the mentioned earthquake. The first method detects unusual variations, 9 days before the event, between 21:00 and 22:00 UTC. The other two methods of Kalman filter and Neural Network detect another clear anomaly on 11 days preceding the earthquake at 16:00 UTC. These findings are two of the outstanding results of GPS-TEC precursor analysis. This paper also presents the results of Swarm satellites (Alpha, Bravo and Charlie) data analysis inside the Dobrovolsky area around the Iran earthquake epicenter during the period from 1 August to 30 November 2017. The time series and orbital analysis of six measured parameters including electron density, electron temperature, magnetic scalar and vectors (X, Y, Z) components indicate irregular variations between 8 and 11 days prior to the occurrence of the earthquake. Since the variations of the solar and geomagnetic indices follow a normal behaviour during the whole period of the observed ionospheric anomalies between 8 and 11 days before the earthquake, it can be concluded that multi-precursors analysis has an important role to acknowledge the seismo-LAI (Lithospheric-Atmospheric-Ionospheric) anomalies associated to strong earthquakes such as this case. Furthermore, some physical and chemical atmospheric parameters from a climatological database are investigated and some interesting anomalies above two standard deviations prior to the earthquake are found. This paper shows not only anomalies in atmosphere and ionosphere but also a contemporary analysis of different data sources to detect the possible Lithosphere Atmosphere Ionosphere Coupling (LAIC) effects.