摘要
The seismo-electromagnetic(EM)method is an important geophysical method that plays a major role in the observation of seismic anomalies related to earthquake precursors.It is the most promising method for a breakthrough in short-term earthquake prediction.The digital transformation and network upgrading implemented in the“Ninth five-year plan”and“Tenth five-year plan”have optimized the original observation system,improved the quality of observed data,enriched the seismicelectromagnetic information,and enhanced the analysis capability and timeliness of seismic-electromagnetic anomalies.These improvements are of major importance for the research on seismo-electromagnetics as well as for the development of new technologies.Since the beginning of the 21 st century,China has launched a satellite named CSES that was designed for the generation and study of seismo-electromagnetic data and built a high-power transmitting source and a new CSELF observation network that is used specifically for earthquake monitoring.This platform has promoted the full-time three-dimensional EM monitoring and the identification of earthquake anomalies.Based on the study of anomalies related to earthquake precursors,the physical and numerical simulations,and the study on generation mechanism of anomalies in China,we summarize the characteristics of earthquake EM anomalies and discuss the advantages and disadvantages of different EM observation methods.Finally,considering the related questions of the seismo-electromagnetic prediction and implementing the recent developments both in China and abroad,we review the current status of seismo-electromagnetic research and propose strategies for future research.
基金
financially supported by the National Key Research and Development Program of China(Grant Nos.2017YFC1500103&2018YFC1503506)
the Project for Basic Research Work of the Institute of Geology,China Earthquake Administration(Grant No.IGCEA1919)
the National Natural Science Foundation of China(Grant Nos.41374077,42074086&41674156)
the National Major Science and Technology Infrastructure Project(Grant No.15212Z0000001)。
