Document Type
Article
Publication Date
10-1-2024
Abstract
When earthquakes occur in high-mountain areas during the winter season, the epicentral region is often covered by a snow layer, which can be either thin or thick. The presence of snow and/or ice layers affects the detection of thermal anomalies associated with seismic signals. Taking into account the penetration capabilities of microwaves, microwave brightness temperature data were analyzed by using the index of microwave radiation anomaly to study the response of the epicentral region associated with two recent strong earthquakes in Central Asia, which occurred in snow-covered mountainous areas. Increased microwave radiation was observed within one week prior to the earthquakes. By conducting a comparative analysis of different frequencies and a comprehensive examination of meteorological parameters, we distinguished anomalies caused by tectonic activity from those induced by atmospheric water vapor. A robustness analysis from the periods of seismic tranquility and seismic disturbance has been conducted to validate our results. Our findings suggest that regions with less snow cover or shallow snow depth may exhibit high sensitivity to seismic microwave radiation anomalies in high-altitude mountainous areas during the cold season, which can be detected through passive microwave remote sensing. Combined with a further analysis from microwave polarization difference index and distribution of regional lithology, we proposed that the theory of positive holes may be the dominant mechanism for enhanced microwave radiation.
Recommended Citation
F. Jing, M. Jiang and R. P. Singh, "Detection of Seismic Microwave Radiation Anomalies in Snow-Covered Mountainous Terrain: Insights From Two Recent Earthquakes in the Pamir–Tien Shan Region," in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 17, pp. 18156-18166, 2024, https://doi.org/10.1109/JSTARS.2024.3472045.
Peer Reviewed
1
Copyright
The authors
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
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Comments
This article was originally published in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, volume 17, in 2024. https://doi.org/10.1109/JSTARS.2024.3472045