Anomalies in Infrared Outgoing Longwave Radiation Data before the Yangbi Ms6.4 and Luding Ms6.8 Earthquakes Based on Time Series Forecasting Models

Zhu, Jun; Sun, Kaiqiong; Zhang, Jingye

doi:10.3390/app13158572

Cited by 3 publications

(1 citation statement)

References 55 publications

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“…They investigated the observed AEF anomalies and concluded that four negative AEF anomalies are likely associated with the Luding earthquake. Zhu et al [57] studied the outgoing longwave radiation (OLR) data prior to the Luding earthquake.Significant OLR anomalies were detected on August 9, August 18, and August 28 before the Luding earthquake. Liu et al [58] also investigated the anomalies in AEF and OLR before the Luding earthquake, along with examining disturbances in the ionosphere and investigating the anomalies in infrared radiation and hot spring ions.…”

Section: Superposed Epoch Analysis (Sea) For the Geomagnetic Topology...mentioning

confidence: 99%

The Study on Anomalies of the Geomagnetic Topology Network Associated with the 2022 Ms6.8 Luding Earthquake

Yu,

Jing,

Wang

et al. 2024

Remote Sensing

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On 5 September 2022, the Ms 6.8 Luding earthquake occurred at 29.59°N and 102.08°E in China. To investigate the variations in geomagnetic signals before the earthquake, this study analyzes the geomagnetic data from nine stations around the epicenter. First, we apply the Multi-channel Singular Spectrum Analysis to reconstruct the periodic components of the geomagnetic data from multiple stations. Second, we employ K-means clustering to rule out the possibility of occasional anomalies caused by a single station. Subsequently, we construct a geomagnetic topology network considering the remaining stations. Network centrality is defined as a measure of overall network connectivity, where the higher the correlation between multiple stations, the greater the network centrality. Finally, we examine the network centrality 45 days before and 15 days after the Luding earthquake. The results show that several anomalies in network centrality are extracted about one week before the earthquake. We further validate the significance of the anomalies in terms of time as well as space and verify the utility of the centrality anomalies through the SEA technique. The anomalies are found to have a statistical correlation with the earthquake event. We consider that this study provides a new way and a novel observational perspective for earthquake precursor analysis of ground-based magnetic data.

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Section: Superposed Epoch Analysis (Sea) For the Geomagnetic Topology...mentioning

confidence: 99%

The Study on Anomalies of the Geomagnetic Topology Network Associated with the 2022 Ms6.8 Luding Earthquake

Yu,

Jing,

Wang

et al. 2024

Remote Sensing

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Investigation of Atmospheric Anomalies due to the Great Tohoku Earthquake Disturbance Using NRLMSISE-00 Atmospheric Model Measurement

Endeshaw

2024

Pure Appl. Geophys.

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In this study, the atmospheric changes for the 9.0-magnitude Tohoku earthquake, which occurred on March 11, 2011, are analyzed. The March 11, 2011 earthquake was preceded by a large foreshock on March 09, 2011 with magnitude M 7.3 and depth 32 km at 02:45:20 UT near the east coast of Honshu, Japan. The earthquake doesn’t limit its effects on the Earth’s lithosphere, hydrosphere and biosphere; it also extends its effects to the atmosphere because of the gas emissions, which produce large-scale seismic waves from the ground and release gases into the atmosphere. In this study, the anomalies of the atmospheric parameters are studied by using one of the atmospheric models from the Naval Research Laboratory Mass Spectrometer Incoherent Scatter Extension 2000 (NRLMSISE-00) model data to analyze the atmospheric anomalies of the Tohoku Earthquake on March 11, 2011. The atmospheric parameters of atomic oxygen (O), hydrogen (H), atomic nitrogen (N), helium (He), argon (Ar), molecular oxygen (O2), molecular nitrogen (N2), total mass density (ρ), neutral temperature (Tn), exospheric temperature (Tex) and anomalous oxygen (AO) are used for analysis during the earthquake occurrence. The epicenter of the Tohoku earthquake, with a geographical location of latitude 38.30° N and longitude 142.37° E, is used for the NRLMSISE-00 model as input parameters to analyze the output of atmospheric parameters. To compare the atmospheric changes caused by the earthquake, 5 days before and after the earthquake are considered. To detect where the atmospheric parameters increased or decreased from the earthquake day, the percentage deviation of the NRLMSISE-00 model is applied. The results indicate that there were atmospheric parameter anomalies that occurred a few days before, following and during the earthquake on March 11, 2011. Except for hydrogen (H), all atmospheric parameters average daily percentage deviation values were positive during the 5 days before and after with respect to the main earthquake shock on March 11, 2011. The NRLMSISE-00 model can capture the atmospheric parameter anomalies of the Tohoku earthquake well.

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Integrating Computational Wisdom

Rubidha Devi,

Natarajan

2024

Advances in Environmental Engineering and Green Technologies

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This study employs deep learning and machine learning to critically analyze the significance of ensemble approaches in earthquake prediction. It examines research that has utilized ensemble techniques to enhance prediction resilience, emphasizing the value of boosting, bagging, and random forests. The analysis includes a discussion of the impacts of hyperparameter tuning, ensemble diversity, and the combination of multiple models. The chapter highlights the growing trend of merging seismic and non-seismic precursors to improve forecasting capabilities. Advances in data integration techniques and interdisciplinary models are reviewed, along with multidisciplinary approaches that incorporate numerous sources of data. This chapter focuses on the development and deployment of early warning systems that use both seismic and non-seismic data to predict earthquakes. It also suggests the need for standardized data formats and cooperative efforts to overcome difficulties in data integration and standardization.

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Anomalies in Infrared Outgoing Longwave Radiation Data before the Yangbi Ms6.4 and Luding Ms6.8 Earthquakes Based on Time Series Forecasting Models

Cited by 3 publications

References 55 publications

The Study on Anomalies of the Geomagnetic Topology Network Associated with the 2022 Ms6.8 Luding Earthquake

The Study on Anomalies of the Geomagnetic Topology Network Associated with the 2022 Ms6.8 Luding Earthquake

Investigation of Atmospheric Anomalies due to the Great Tohoku Earthquake Disturbance Using NRLMSISE-00 Atmospheric Model Measurement

Integrating Computational Wisdom

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