Temporal-Spatial Characteristics of Seismo-Ionospheric Influences: Observation from the China Seismo-Electromagnetic Satellite (CSES)

Significance 

The ionosphere, a crucial layer of Earth’s upper atmosphere, exhibits complex behaviors influenced by various geophysical processes, including seismic activities. Detecting and analyzing ionospheric perturbations associated with strong earthquakes can provide critical insights into the precursory signals that precede seismic events. Indeed seismo-ionospheric influences are increasingly important due to its potential implications for earthquake prediction and understanding lithosphere-atmosphere-ionosphere coupling (LAIC) mechanisms. The main challenges in studying seismo-ionospheric influences stem from the complexity and variability of the ionosphere, which is affected by a multitude of factors including solar activity, geomagnetic storms, and diurnal variations. These influences can mask the subtle ionospheric perturbations caused by seismic activities, making it difficult to isolate and identify earthquake-induced anomalies. Specific challenges include Data complexity and volume, Temporal and spatial variability, Environmental noise and sensor limitation. To this end, new study published in Journal of Advances in Space Research and led by Professor Mei Li, Senior engineer Xianghua Jiang, Senior engineer Jiefei Li, Professor Yongxian Zhang, from the China Earthquake Administration and Professor Xuhui Shen, from the Chinese Academy of Sciences, leveraged the capabilities of the China Seismo-Electromagnetic Satellite (CSES) to investigate the temporal-spatial characteristics of seismo-ionospheric influences.

The researchers used data from the CSES, which orbits at a height of 500 km and provides comprehensive global coverage. The satellite is equipped with several instruments, including a Langmuir probe (LAP) for measuring electron density (Ne) and a plasma analyzer package (PAP) for ion density (Ni). The data covered a period from August 2018 to December 2021, offering over three years of continuous measurements. To ensure data reliability, the team applied the Savitzky-Golay smoothing filter to eliminate noise and pulse-like peaks. They utilized an automated software to identify perturbations within a specified spatial scale (20–300 seconds) and without limit on amplitude range. The authors showed the processed data revealed 96,863 electron perturbations and 111,908 ion perturbations. Notably, electron density varied almost equally between daytime (46.5%) and nighttime (53.5%), while ion density variations were predominantly nighttime (77.5%). This indicated that ion density is more sensitive to nocturnal conditions, which aligns with the increased detection rate of seismic activities during nighttime. The researchers performed a detailed temporal-spatial analysis of the detected ionospheric perturbations, and focused on both their temporal occurrence and spatial distribution relative to seismic events. The authors’ temporal analysis demonstrated that ionospheric anomalies predominantly appeared within 5 days before significant earthquakes, which supports previous studies that indicated a similar timeframe for seismo-ionospheric precursors. Spatially, the anomalies were often found 500–700 km away from the earthquake epicenters rather than directly above them. This spatial shift is consistent with the theoretical model of zonal electric fields propagating along magnetic lines, which displaces the ionospheric response from the epicenter.

To examine the sensitivity of ionospheric perturbations to seismic activities, the team analyzed the amplitude and spatial scale of the detected anomalies. They categorized perturbations into different amplitude ranges (e.g., <20%, 20–70%, >70%) and spatial scales (e.g., 20–120 seconds, 120–200 seconds). According to the authors, perturbations with amplitudes (<100%) and spatial scales (20–120 seconds) were more frequently associated with seismic activities, particularly for electron density. Additionally, the analysis highlighted that large variations (>100%) primarily revealed large-scale ionospheric structures and were rarely directly related to seismic events. To validate their findings, the researchers compared the results with randomly generated earthquake points, which was crucial to differentiate genuine seismic-induced anomalies from coincidental perturbations. The comparison with random earthquake data significantly differed from the actual earthquake data. This validation confirmed that the observed anomalies were indeed related to seismic activities and not random occurrences.

The study also considered the impact of geomagnetic activity on ionospheric perturbations. By keeping the Kp index below 3 during the analysis period, the researchers minimized the influence of solar and geomagnetic activities, focusing on seismo-ionospheric effects. The authors’ analysis confirmed that geomagnetic storms had a global effect on ionospheric conditions, with significant disturbances observed during high Kp index periods. However, with restricting the Kp index, the study successfully isolated seismic-induced anomalies and demonstrated that these anomalies are more pronounced when geomagnetic activity is low. This finding is critical for distinguishing between perturbations caused by solar activities and those related to seismic events.

In conclusion, Professor Mei Li and colleagues from the China Earthquake Administration enhanced our understanding of seismo-ionospheric influences and their potential applications in earthquake prediction. Moreover, the new study provided robust evidence supporting the LAIC mechanisms. The new study enhances our understanding of how energy transfers between Earth’s layers and affects ionospheric conditions by identifying the temporal and spatial patterns of ionospheric perturbations associated with seismic activities. Furthermore, the observed spatial shift of ionospheric anomalies 500–700 km from earthquake epicenters aligns with theoretical models of zonal electric fields propagating along magnetic lines. This validation strengthens the credibility of these models and provides a foundation for further theoretical development. Additionally, the identification of ionospheric anomalies predominantly occurring within 5 days before significant earthquakes is a critical finding. This temporal pattern offers a potential early warning signal, contributing to the development of more reliable earthquake prediction methods. Indeed, the findings of Professor Mei Li and colleagues can be integrated into existing earthquake prediction frameworks to enhance their accuracy and with incorporating ionospheric data as a precursor signal, the new predictive models can provide earlier and more reliable warnings which potentially can save lives and reduce economic losses. In addition, the better prediction of earthquakes can have significant implications for policy-making and emergency preparedness with disaster response agencies implement timely evacuation plans, reinforce infrastructure, and allocate resources more effectively.

Temporal-Spatial Characteristics of Seismo-Ionospheric Influences: Observation from the China Seismo-Electromagnetic Satellite (CSES) - Advances in Engineering Temporal-Spatial Characteristics of Seismo-Ionospheric Influences: Observation from the China Seismo-Electromagnetic Satellite (CSES) - Advances in Engineering Temporal-Spatial Characteristics of Seismo-Ionospheric Influences: Observation from the China Seismo-Electromagnetic Satellite (CSES) - Advances in Engineering Temporal-Spatial Characteristics of Seismo-Ionospheric Influences: Observation from the China Seismo-Electromagnetic Satellite (CSES) - Advances in Engineering

About the author

Mei Li serves as Professor in the Research Division of Short-term Earthquake Forecasting, Institute of Earthquake Forecasting, China Earthquake Administration, since 2023. During 2004–2022, she worked in the Earthquake Forecasting Department, China Earthquake Networks Center, China Earthquake Administration. From 2011 to 2012, she pursued research on ionospheric precursors from DEMETER satellite in LPC2E/CNRS in France.

She received the B.S. degree in geophysics from Jianghan Petroleum University in 2000, and the M.S. and Ph.D. degrees in geophysics from China University of Geosciences (Beijing) in 2004 and 2015, respectively. Her research interests cover electromagnetic emissions associated with seismic activities, seismo-ionospheric influence and space weather, and lithosphere-atmosphere-ionosphere electromagnetic coupling (LAIEC) mechanism and modeling. As an academic leader of satellite measurement, she has put the plasma data recorded by the CSES satellite into earthquake forecasting practice in China since 2020 and positive results have been attained.

About the author

Xianghua Jiang serves as Senior Engineer in the Earthquake Forecasting Department, China Earthquake Networks Center, China Earthquake Administration.

He received the B.S. degree in geophysics and the Ph.D. degree in solid geophysics from School of Earth and Space Science, Peking University in 2009 and 2015, respectively. His research interests focuses on seismicity and earthquake precursors.

About the author

Jiefei Li works as Head of Comprehensive Department of Earthquake Forecasting and Network Technology Support. He received the B.S. degree in applied geophysics and engineering seismology from Institute of Disaster Prevention in 1997 and the M.S. degree in land resource management from Hunan Normal University in 2008. His work involves earthquake monitoring, forecasting and warning, earthquake information networks and security, and construction of basic platforms.

About the author

Yongxian Zhang works as Professor and Head in the Research Division of Short-term Earthquake Forecasting, Institute of Earthquake Forecasting, China Earthquake Administration, Deputy chairman of the APEC Cooperation for Earthquake Science, and Executive Director Boarder member of China Seismological Society. She visited UC Davis of USA as a senior visiting scholar in 2012. Her study interests are modeling of seismogenic processes, seismicity patterns, earthquake anomaly mechanisms, synthetic methods of earthquake forecasting, and predictability testing. She has published more than 100 papers and 8 works. She won several national awards in China such as National Excellent Scientist from China Association for Science and Technology, Special allowance of the State Council of China, etc.

About the author

Xuhui Shen serves as Professor in the State Key Lab of Solar Activity and Space Weather, National Space Science Center, Chinese Academy of Sciences since 2022. He worked separately in the Institute of earthquake Forecasting and the Institute of Crustal Dynamics of China Earthquake Administration and took the duties of the Head Scientist and Deputy-Designer-in-general of the CSES mission in the last 20 years. He received his Master degree separately in 1990 and PhD in 1996 in the Institute of Geology, China Earthquake Administration. His main research area includes space geophysics, remote sensing application in natural hazard mitigation and lithosphere-atmosphere-ionosphere coupling.

Reference

Mei Li, Xianghua Jiang, Jiefei Li, Yongxian Zhang, Xuhui Shen, Temporal-spatial characteristics of seismo-ionospheric influence observed by the CSES satellite, Advances in Space Research, Volume 73, Issue 1, 2024, Pages 607–623,

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