Lithosphere-Atmosphere-Ionosphere Coupling during Earthquake Preparation
Recent Advances and Future Perspectives
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This Reprint is concerned with the problems of earthquake (EQ) precursors, short-term EQ prediction, and related fundamental scientific physics. EQ prediction (especially short-term prediction) is one of the most challenging subjects in the field of geosciences, and in the last few decades, researchers have achieved a lot of significant progress in various EQ precursors found not only in the lithosphere but also in the atmosphere and ionosphere. Further, the uppermost layer of ionosphere is found to be very sensitive to pre-EQ lithospheric activity, according to data from subionospheric VLF/LF...
This Reprint is concerned with the problems of earthquake (EQ) precursors, short-term EQ prediction, and related fundamental scientific physics. EQ prediction (especially short-term prediction) is one of the most challenging subjects in the field of geosciences, and in the last few decades, researchers have achieved a lot of significant progress in various EQ precursors found not only in the lithosphere but also in the atmosphere and ionosphere. Further, the uppermost layer of ionosphere is found to be very sensitive to pre-EQ lithospheric activity, according to data from subionospheric VLF/LF propagation, ionosonde, and TEC observations, as well as satellite in situ observations, leading to the generation of a new intrinsic concept of lithosphere-atmosphere-ionosphere coupling (LAIC). Several hypotheses have already been proposed to explain the LAIC process by making full use of satellite- and ground-based multi-parameter observations, but we are still far from having a complete understanding, and this topic needs further extensive investigation. This Reprint offers new contributions to the LAIC process by presenting 12 papers, most of which deal with the latest findings and achievements related to the study of the LAIC process based on multi-parameter and multi-layer observations, and one of them recommends the use of artificial intelligence in the identification of EQ precursors. We hope that this Reprint will provide you with a new direction for short-term EQ prediction studies and encourage the production of further extensive seismo-electromagnetic studies in the future.
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