Abstract

Taking the 2017 Mw6.5 Jiuzhaigou earthquake as a case study, ionospheric disturbances (i.e., total electron content and TEC) and thermal infrared (TIR) anomalies were simultaneously investigated. The characteristics of the temperature of brightness blackbody (TBB), medium-wave infrared brightness (MIB), and outgoing longwave radiation (OLR) were extracted and compared with the characteristics of ionospheric TEC. We observed different relationships among the three types of TIR radiation according to seismic or aseismic conditions. A wide range of positive TEC anomalies occurred southern to the epicenter. The area to the south of the Huarong mountain fracture, which contained the maximum TEC anomaly amplitudes, overlapped one of the regions with notable TIR anomalies. We observed three stages of increasing TIR radiation, with ionospheric TEC anomalies appearing after each stage, for the first time. There was also high spatial correspondence between both TIR and TEC anomalies and the regional geological structure. Together with the time series data, these results suggest that TEC anomaly genesis might be related to increasing TIR.

Highlights

  • Electromagnetic signals can spread from the lithosphere to the atmosphere and ionosphere via electromagnetic, acoustic, and geochemical pathways, and models for “lithosphere—atmosphere—ionosphere” coupling (LAIC) during electromagnetic propagation have been experimentally derived [1,2,3,4]

  • In the late 1980s, Soviet scientists discovered preseismic infrared radiation anomalies when analyzing earthquake activity in the Middle East [5]; since many studies have investigated seismic infrared anomalies and found that during the process of energy accumulation and release, the crustal structure can be coupled with changes in ground thermal infrared radiation [6,7,8,9,10,11,12]: e.g., rock testing was made in laboratory, the observed enhanced mid-IR emission is believed to arise based on some physical mechanism; the complex analysis of TIR satellite data demonstrated that the transient TIR anomalies starts along the main tectonic fault zone and variations could be seen in a radius of approximately 100 km around the epicenter over the land and sea

  • He et al [34] studied the changes in electron density before and after 7000 global Ms ≥ 5 earthquakes from 2006 to 2009 using DEMETER (Detection of Electro-Magnetic Emission Transmitted from Earthquakes) data; they found that preseismic anomalies were always concentrated near epicenters

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Summary

Introduction

Electromagnetic signals can spread from the lithosphere to the atmosphere and ionosphere via electromagnetic, acoustic, and geochemical pathways, and models for “lithosphere—atmosphere—ionosphere” coupling (LAIC) during electromagnetic propagation have been experimentally derived [1,2,3,4]. Liu and Wan [33] used GPS TEC to analyze Ms ≥ 6 earthquakes in China from 1998 to 2010 and found that abnormal disturbances occurred in multiple directions around epicenters in the 3–5 days before an earthquake He et al [34] studied the changes in electron density before and after 7000 global Ms ≥ 5 earthquakes from 2006 to 2009 using DEMETER (Detection of Electro-Magnetic Emission Transmitted from Earthquakes) data; they found that preseismic anomalies were always concentrated near epicenters. Zhai [42] used Global Navigation Satellite System (GNSS) data for reference stations of a land-based network to compare and analyze ionospheric TEC anomalies of the Songpan station (Sichuan province) using an IQR method and the Prophet model; the results showed three positive anomalies (the 7th day before the earthquake and the 1st day and the 7th day after the earthquake) and three negative anomalies (the 10th day, 2nd day before the earthquake, and the 6th day after the earthquake). In this study, infrared data of different wavebands observed by the same satellite at the same time were compared so as to objectively understand earthquake-related thermal infrared anomalies

Infrared Data and Methods
TEC Data and Methods
Results and Discussion
Comparison of Anomalous Infrared Power Spectra
Conclusions
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