岩石圈
电离层
地质学
地震学
大气(单位)
地球物理学
气象学
构造学
地理
作者
Ching‐Chou Fu,Hao Kuo‐Chen,Chung‐Hsiang Mu,Hau-Kun Jhuang,L. C. Lee,Vivek Walia,Tsung-Che Tsai
标识
DOI:10.5194/egusphere-egu25-8052
摘要
This study conducted a systematic analysis of the 2022 Chihshang earthquake sequence in eastern Taiwan, integrating multidimensional observational parameters related to the lithosphere, atmosphere, and ionosphere. High-resolution data from the MAGIC (Multidimensional Active fault of Geo-Inclusive observatory - Chihshang) at the Chihshang fault area provided a comprehensive and diverse dataset. The analysis revealed significant pre-earthquake anomalies across various parameters. These include a marked increase in soil radon concentration one month prior to the earthquake, concurrent anomalies in hydrogeochemical parameters (e.g., elevated groundwater temperature, reduced pH, and decreased chloride ion concentration), and active foreshock activity detected by a dense microseismic network starting mid-August, suggesting the development of microfractures within the lithosphere. Additionally, persistent OLR (Outgoing Longwave Radiation) anomalies, indicating hotspots near the epicenter, were observed from September 5 to 7. Pre-earthquake signals in TEC (Total Electron Content) were identified between August 20 and September 13 in two independent datasets, GIM-TEC and CWA-TEC.Post-earthquake observations revealed a significant increase in CO2 flux in the region, likely attributable to the release of deep-seated gas sources or enhanced permeability of the fault system. These combined observations suggest that all anomalies can be classified as short-term precursors, which can be interpreted within the theoretical framework of lithosphere-atmosphere-ionosphere coupling (LAIC). The findings also contribute to a deeper understanding of the earthquake preparation process. This study underscores the critical importance of real-time integration of multi-parameter observations, offering new insights and improvements for seismic hazard assessment and advancing the predictive capability of earthquake precursors.
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